@article{zhong2025narrative,
  title={A Narrative Review on Large AI Models in Lung Cancer Screening, Diagnosis, and Treatment Planning},
  author={Zhong, Jiachen and Wang, Yiting and Zhu, Di and Wang, Ziwei},
  journal={arXiv preprint arXiv:2506.07236},
  year={2025}
}

@inproceedings{zhang2023clip,
  title={CLIP Model for Images to Textual Prompts Based on Top-k Neighbors},
  author={Zhang, Xin and Kang, Hui and Cai, Yeming and Jia, Tianzhi},
  booktitle={2023 3rd International Conference on Electronic Information Engineering and Computer Science (EIECS)},
  pages={821--824},
  year={2023},
  organization={IEEE}
}

@article{zhu2022motion,
  title={Motion capture data denoising based on LSTNet autoencoder},
  author={Zhu, Yong-Qiong and Cai, Ye-Ming and Zhang, Fan},
  journal={Journal of Internet Technology},
  volume={23},
  number={1},
  pages={11--20},
  year={2022}
}

@inproceedings{zhou2023image,
  title={Image retrieve for dolphins and whales based on EfficientNet network},
  author={Zhou, Tong and Li, Shengyang and Bo, Tian and Cai, Yeming},
  booktitle={Sixth International Conference on Computer Information Science and Application Technology (CISAT 2023)},
  volume={12800},
  pages={1239--1244},
  year={2023},
  organization={SPIE}
}

@article{zhong2025enhancing,
  title={Enhancing Thyroid Disease Prediction Using Machine Learning: A Comparative Study of Ensemble Models and Class Balancing Techniques},
  author={Zhong, Jiachen and Wang, Yiting},
  year={2025}
}

@article{ke2025detection,
  title={Detection of ai deepfake and fraud in online payments using gan-based models},
  author={Ke, Zong and Zhou, Shicheng and Zhou, Yining and Chang, Chia Hong and Zhang, Rong},
  journal={arXiv preprint arXiv:2501.07033},
  year={2025}
}

@article{you2025mirage,
  title={MIRAGE: Multimodal Immersive Reasoning and Guided Exploration for Red-Team Jailbreak Attacks},
  author={You, Wenhao and Hooi, Bryan and Wang, Yiwei and Wang, Youke and Ke, Zong and Yang, Ming-Hsuan and Huang, Zi and Cai, Yujun},
  journal={arXiv preprint arXiv:2503.19134},
  year={2025}
}

@inproceedings{lirevolutionizing,
  title={Revolutionizing Drug Discovery: Integrating Spatial Transcriptomics with Advanced Computer Vision Techniques},
  author={Li, Zichao and Qiu, Shiqing and Ke, Zong},
  booktitle={1st CVPR Workshop on Computer Vision For Drug Discovery (CVDD): Where are we and What is Beyond?}
}

@article{zhao2023noncovanm,
  title={NoncovANM: Gridless DOA estimation for LPDF system},
  author={Zhao, Yangying and Chen, Peng and Cao, Zhenxin and Wang, Xianbin},
  journal={IEEE Transactions on Vehicular Technology},
  volume={72},
  number={12},
  pages={15563--15573},
  year={2023},
  publisher={IEEE}
}

@article{zhao2023ris,
  title={RIS-aided sensing system with localization function: Fundamental and practical design},
  author={Zhao, Yangying and Chen, Peng and Sun, Mengjiang and Luo, Tao and Cao, Zhenxin},
  journal={IEEE Sensors Journal},
  volume={24},
  number={1},
  pages={506--514},
  year={2023},
  publisher={IEEE}
}


@article{zhao2024nflnet,
  title={NFLnet: A Deep Neural Network-Based Localization Method for Near-Field Vehicles},
  author={Zhao, Yangying and Chen, Peng and Cao, Zhenxin},
  journal={IEEE Transactions on Instrumentation and Measurement},
  year={2024},
  publisher={IEEE}
}


@inproceedings{li2024research,
  title={Research on reinforcement learning based warehouse robot navigation algorithm in complex warehouse layout},
  author={Li, Keqin and Liu, Lipeng and Chen, Jiajing and Yu, Dezhi and Zhou, Xiaofan and Li, Ming and Wang, Congyu and Li, Zhao},
  booktitle={2024 6th International Conference on Artificial Intelligence and Computer Applications (ICAICA)},
  pages={296--301},
  year={2024},
  organization={IEEE}
}


@article{mao2025research,
  title={Research and Design on Intelligent Recognition of Unordered Targets for Robots Based on Reinforcement Learning},
  author={Mao, Yiting and Tao, Dajun and Zhang, Shengyuan and Qi, Tian and Li, Keqin},
  journal={arXiv preprint arXiv:2503.07340},
  year={2025}
}


@article{yang2024tcellsi,
  title={TCellSI: A novel method for T cell state assessment and its applications in immune environment prediction},
  author={Yang, Jing-Min and Zhang, Nan and Luo, Tao and Yang, Mei and Shen, Wen-Kang and Tan, Zhen-Lin and Xia, Yun and Zhang, Libin and Zhou, Xiaobo and Lei, Qian and others},
  journal={Imeta},
  volume={3},
  number={5},
  pages={e231},
  year={2024},
  publisher={Wiley Online Library}
}

@inproceedings{yu2024identifying,
  title={Identifying money laundering risks in digital asset transactions based on ai algorithms},
  author={Yu, Qian and Ke, Zong and Xiong, Guofu and Cheng, Yu and Guo, Xiaojun},
  booktitle={2024 4th International Conference on Electronic Information Engineering and Computer Communication (EIECC)},
  pages={1081--1085},
  year={2024},
  organization={IEEE}
}


@article{demir2021deepcoronet,
  title={DeepCoroNet: A deep LSTM approach for automated detection of COVID-19 cases from chest X-ray images},
  author={Demir, Fatih},
  journal={Applied soft computing},
  volume={103},
  pages={107160},
  year={2021},
  publisher={Elsevier}
}

@article{islam2020combined,
  title={A combined deep CNN-LSTM network for the detection of novel coronavirus (COVID-19) using X-ray images},
  author={Islam, Md Zabirul and Islam, Md Milon and Asraf, Amanullah},
  journal={Informatics in medicine unlocked},
  volume={20},
  pages={100412},
  year={2020},
  publisher={Elsevier}
}

@article{kalane2021automatic,
  title={Automatic detection of COVID-19 disease using U-Net architecture based fully convolutional network},
  author={Kalane, Prasad and Patil, Sarika and Patil, BP and Sharma, Davinder Pal},
  journal={Biomedical Signal Processing and Control},
  volume={67},
  pages={102518},
  year={2021},
  publisher={Elsevier}
}

@article{bukhari2020diagnostic,
  title={The diagnostic evaluation of Convolutional Neural Network (CNN) for the assessment of chest X-ray of patients infected with COVID-19},
  author={Bukhari, Syed Usama Khalid and Bukhari, Syed Safwan Khalid and Syed, Asmara and Shah, Syed Sajid Hussain},
  journal={MedRxiv},
  pages={2020--03},
  year={2020},
  publisher={Cold Spring Harbor Laboratory Press}
}

@article{su2023improved,
  title={An improved BERT method for the evolution of network public opinion of major infectious diseases: Case Study of COVID-19},
  author={Su, Meng and Cheng, Dongsheng and Xu, Yan and Weng, Futian},
  journal={Expert Systems with Applications},
  volume={233},
  pages={120938},
  year={2023},
  publisher={Elsevier}
}

@inproceedings{barman2024detecting,
  title={Detecting Infectious Disease Based on Social Media Data Using BERT Model},
  author={Barman, Rajarshi and Rajamohan, Kavitha},
  booktitle={2024 IEEE International Conference on Contemporary Computing and Communications (InC4)},
  volume={1},
  pages={1--6},
  year={2024},
  organization={IEEE}
}


@article{centres2024diffusion,
  title={Diffusion model for the spread of infectious diseases: SIR model with mobile agents},
  author={Centres, PM and Perez-Morelo, DJ and Guzman, R and Reinaudi, L and Gimenez, MC},
  journal={Physica A: Statistical Mechanics and its Applications},
  volume={633},
  pages={129399},
  year={2024},
  publisher={Elsevier}
}

@article{kim2020automated,
  title={Automated classification of online sources for infectious disease occurrences using machine-learning-based natural language processing approaches},
  author={Kim, Mira and Chae, Kyunghee and Lee, Seungwoo and Jang, Hong-Jun and Kim, Sukil},
  journal={International Journal of Environmental Research and Public Health},
  volume={17},
  number={24},
  pages={9467},
  year={2020},
  publisher={MDPI}
}


@article{erraguntla2019framework,
  title={Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management},
  author={Erraguntla, Madhav and Zapletal, Josef and Lawley, Mark},
  journal={Health informatics journal},
  volume={25},
  number={4},
  pages={1170--1187},
  year={2019},
  publisher={SAGE Publications Sage UK: London, England}
}


@article{cheng2023potential,
  title={Potential use of artificial intelligence in infectious disease: take ChatGPT as an example},
  author={Cheng, Kunming and Li, Zhiyong and He, Yongbin and Guo, Qiang and Lu, Yanqiu and Gu, Shuqin and Wu, Haiyang},
  journal={Annals of biomedical engineering},
  volume={51},
  number={6},
  pages={1130--1135},
  year={2023},
  publisher={Springer}
}

@article{chandra2022deep,
  title={Deep learning via LSTM models for COVID-19 infection forecasting in India},
  author={Chandra, Rohitash and Jain, Ayush and Singh Chauhan, Divyanshu},
  journal={PloS one},
  volume={17},
  number={1},
  pages={e0262708},
  year={2022},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{absar2022efficacy,
  title={The efficacy of deep learning based LSTM model in forecasting the outbreak of contagious diseases},
  author={Absar, Nurul and Uddin, Nazim and Khandaker, Mayeen Uddin and Ullah, Habib},
  journal={Infectious Disease Modelling},
  volume={7},
  number={1},
  pages={170--183},
  year={2022},
  publisher={Elsevier}
}

@article{pranolo2021cae,
  title={CAE-COVIDX: automatic covid-19 disease detection based on x-ray images using enhanced deep convolutional and autoencoder.},
  author={Pranolo, Andri and Mao, Yingchi and others},
  journal={International Journal of Advances in Intelligent Informatics},
  volume={7},
  number={1},
  year={2021}
}

@article{mansour2021unsupervised,
  title={Unsupervised deep learning based variational autoencoder model for COVID-19 diagnosis and classification},
  author={Mansour, Romany F and Escorcia-Gutierrez, Jos{\'e} and Gamarra, Margarita and Gupta, Deepak and Castillo, Oscar and Kumar, Sachin},
  journal={Pattern Recognition Letters},
  volume={151},
  pages={267--274},
  year={2021},
  publisher={Elsevier}
}


@article{mehta2021classification,
  title={Classification of X-ray images into COVID-19, pneumonia, and TB using cGAN and fine-tuned deep transfer learning models},
  author={Mehta, Tirth and Mehendale, Ninad},
  journal={Research on Biomedical Engineering},
  volume={37},
  pages={803--813},
  year={2021},
  publisher={Springer}
}


@article{albahli2020efficient,
  title={Efficient GAN-based Chest Radiographs (CXR) augmentation to diagnose coronavirus disease pneumonia},
  author={Albahli, Saleh},
  journal={International journal of medical sciences},
  volume={17},
  number={10},
  pages={1439},
  year={2020}
}

@article{motamed2021randgan,
  title={RANDGAN: randomized generative adversarial network for detection of COVID-19 in chest X-ray},
  author={Motamed, Saman and Rogalla, Patrik and Khalvati, Farzad},
  journal={Scientific Reports},
  volume={11},
  number={1},
  pages={8602},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@article{puleio2021recurrent,
  title={Recurrent neural network ensemble, a new instrument for the prediction of infectious diseases},
  author={Puleio, Alessandro},
  journal={The European Physical Journal Plus},
  volume={136},
  number={3},
  pages={319},
  year={2021},
  publisher={Springer Berlin Heidelberg}
}


@inproceedings{liang2016cnn,
  title={CNN-based image analysis for malaria diagnosis},
  author={Liang, Zhaohui and Powell, Andrew and Ersoy, Ilker and Poostchi, Mahdieh and Silamut, Kamolrat and Palaniappan, Kannappan and Guo, Peng and Hossain, Md Amir and Sameer, Antani and Maude, Richard James and others},
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  pages={493--496},
  year={2016},
  organization={IEEE}
}

@article{hira2021automatic,
  title={An automatic approach based on CNN architecture to detect Covid-19 disease from chest X-ray images},
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  journal={Applied Intelligence},
  volume={51},
  pages={2864--2889},
  year={2021},
  publisher={Springer}
}


@article{bharati2021co,
  title={CO-ResNet: Optimized ResNet model for COVID-19 diagnosis from X-ray images},
  author={Bharati, Subrato and Podder, Prajoy and Mondal, M Rubaiyat Hossain and Prasath, VB Surya},
  journal={International Journal of Hybrid Intelligent Systems},
  volume={17},
  number={1-2},
  pages={71--85},
  year={2021},
  publisher={SAGE Publications Sage UK: London, England}
}



@article{showkat2022efficacy,
  title={Efficacy of Transfer Learning-based ResNet models in Chest X-ray image classification for detecting COVID-19 Pneumonia},
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  journal={Chemometrics and Intelligent Laboratory Systems},
  volume={224},
  pages={104534},
  year={2022},
  publisher={Elsevier}
}

@article{farooq2020covid,
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  year={2020}
}


@article{yoshikawa2022can,
  title={Can naive Bayes classifier predict infection in a close contact of COVID-19? A comparative test for predictability of the predictive model and healthcare workers in Japan},
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  number={6},
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  year={2022},
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}

@article{dogantekin2009automatic,
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@article{sartakhti2012hepatitis,
  title={Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA)},
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@article{ramon2022extreme,
  title={eXtreme Gradient Boosting-based method to classify patients with COVID-19},
  author={Ram{\'o}n, Antonio and Torres, Ana Maria and Milara, Javier and Casc{\'o}n, Joaqu{\'\i}n and Blasco, Pilar and Mateo, Jorge},
  journal={Journal of Investigative Medicine},
  volume={70},
  number={7},
  pages={1472--1480},
  year={2022},
  publisher={SAGE Publications Sage CA: Los Angeles, CA}
}

@article{agarwal2022preparing,
  title={Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction},
  author={Agarwal, Khushbu and Choudhury, Sutanay and Tipirneni, Sindhu and Mukherjee, Pritam and Ham, Colby and Tamang, Suzanne and Baker, Matthew and Tang, Siyi and Kocaman, Veysel and Gevaert, Olivier and others},
  journal={Scientific reports},
  volume={12},
  number={1},
  pages={10748},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@inproceedings{wan2021multi,
  title={Multi-objective model-based reinforcement learning for infectious disease control},
  author={Wan, Runzhe and Zhang, Xinyu and Song, Rui},
  booktitle={Proceedings of the 27th ACM SIGKDD conference on knowledge discovery \& data mining},
  pages={1634--1644},
  year={2021}
}

@article{shaier2021data,
  title={Data-driven approaches for predicting spread of infectious diseases through DINNs: Disease Informed Neural Networks},
  author={Shaier, Sagi and Raissi, Maziar and Seshaiyer, Padmanabhan},
  journal={arXiv preprint arXiv:2110.05445},
  year={2021}
}

@article{shaban2020new,
  title={A new COVID-19 Patients Detection Strategy (CPDS) based on hybrid feature selection and enhanced KNN classifier},
  author={Shaban, Warda M and Rabie, Asmaa H and Saleh, Ahmed I and Abo-Elsoud, MA},
  journal={Knowledge-Based Systems},
  volume={205},
  pages={106270},
  year={2020},
  publisher={Elsevier}
}


@inproceedings{nikhil2024revolutionizing,
  title={Revolutionizing Influenza A Detection in Humans: Unleashing the Power of XGBoost Classification},
  author={Nikhil, V and Mary, SA Sahaaya Arul and Natarajan, B and Bajulunisha, A and Anuradha, RS and Venkatraman, K},
  booktitle={2024 IEEE International Conference for Women in Innovation, Technology \& Entrepreneurship (ICWITE)},
  pages={229--234},
  year={2024},
  organization={IEEE}
}

@inproceedings{indhumathi2022seasonal,
  title={Seasonal Infectious Disease Prediction based on Electronic Patient Health Records using Boosted Random Forest Algorithms},
  author={Indhumathi, K and Kumar, K Sathesh},
  booktitle={2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)},
  pages={2025--2032},
  year={2022},
  organization={IEEE}
}

@article{tang2024mtvqa,
  title={Mtvqa: Benchmarking multilingual text-centric visual question answering},
  author={Tang, Jingqun and Liu, Qi and Ye, Yongjie and Lu, Jinghui and Wei, Shu and Lin, Chunhui and Li, Wanqing and Mahmood, Mohamad Fitri Faiz Bin and Feng, Hao and Zhao, Zhen and others},
  journal={arXiv preprint arXiv:2405.11985},
  year={2024}
}

@article{zhao2024harmonizing,
  title={Harmonizing visual text comprehension and generation},
  author={Zhao, Zhen and Tang, Jingqun and Wu, Binghong and Lin, Chunhui and Wei, Shu and Liu, Hao and Tan, Xin and Zhang, Zhizhong and Huang, Can and Xie, Yuan},
  journal={arXiv preprint arXiv:2407.16364},
  year={2024}
}

@inproceedings{zhao2024multi,
  title={Multi-modal in-context learning makes an ego-evolving scene text recognizer},
  author={Zhao, Zhen and Tang, Jingqun and Lin, Chunhui and Wu, Binghong and Huang, Can and Liu, Hao and Tan, Xin and Zhang, Zhizhong and Xie, Yuan},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={15567--15576},
  year={2024}
}


@inproceedings{tang2022optimal,
  title={Optimal boxes: boosting end-to-end scene text recognition by adjusting annotated bounding boxes via reinforcement learning},
  author={Tang, Jingqun and Qian, Wenming and Song, Luchuan and Dong, Xiena and Li, Lan and Bai, Xiang},
  booktitle={European Conference on Computer Vision},
  pages={233--248},
  year={2022},
  organization={Springer}
}


@inproceedings{tang2022few,
  title={Few could be better than all: Feature sampling and grouping for scene text detection},
  author={Tang, Jingqun and Zhang, Wenqing and Liu, Hongye and Yang, MingKun and Jiang, Bo and Hu, Guanglong and Bai, Xiang},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4563--4572},
  year={2022}
}


@article{weng2024fortifying,
  title={Fortifying the global data fortress: a multidimensional examination of cyber security indexes and data protection measures across 193 nations},
  author={Weng, Yijie and Wu, Jianhao and others},
  journal={International Journal of Frontiers in Engineering Technology},
  volume={6},
  number={2},
  pages={13--28},
  year={2024},
  publisher={Francis Academic Press}
}

@article{weng2024leveraging,
  title={Leveraging artificial intelligence to enhance data security and combat cyber attacks},
  author={Weng, Yijie and Wu, Jianhao},
  journal={Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023},
  volume={5},
  number={1},
  pages={392--399},
  year={2024}
}


@article{weng2024comprehensive,
  title={Comprehensive overview of artificial intelligence applications in modern industries},
  author={Weng, Yijie and Wu, Jianhao and Kelly, Tara and Johnson, William},
  journal={arXiv preprint arXiv:2409.13059},
  year={2024}
}

@article{zhao2025role,
  title={The Role of the Major Histocompatibility Complex Region on Chromosome 6 in Skin Atrophy: A Mendelian Randomization Study},
  author={Zhao, Chenyu and Fan, Zhonghao and Zhang, Ruihan and Sun, Yuehang and Li, Wen-Yang},
  journal={Journal of Cosmetic Dermatology},
  volume={24},
  number={3},
  pages={e70040},
  year={2025},
  publisher={Wiley Online Library}
}

@article{zhang2024adaptive,
  title={Adaptive Music Recommendation: Applying Machine Learning Algorithms Using Low Computing Device},
  author={Zhang, Tianhui and Liu, Xianchen and Guo, Zhen and Tian, Yuanhao},
  journal={Journal of Software Engineering and Applications},
  volume={17},
  number={11},
  pages={817--831},
  year={2024},
  publisher={Scientific Research Publishing}
}

@article{parker2024mapping,
  title={Mapping the Molecular Progression of Human Coronary Atherosclerosis Confirms Key Role of Smooth Muscle Cell Phenotype and Highlights Novel Regulators of Phenotypic Fate},
  author={Parker, Sarah and Mao, Chunhong and Wang, Yizhi and Seals, Austin and Kim, Do-Kyun and Lu, Yingzhou and bhardwaj, saurabh and Du, Dongping and Karere, Genesio and Caudell, David and others},
  journal={Circulation},
  volume={150},
  number={Suppl\_1},
  pages={A4139230--A4139230},
  year={2024},
  publisher={Lippincott Williams \& Wilkins Hagerstown, MD}
}

@article{nguyen2024absence,
  title={Absence of SMARCB1 in rhabdoid tumor cells increases sensitivity to translation inhibition and alters translation efficiency of specific mRNAs},
  author={Nguyen, Linh T and Hains, Anastasia E and Aziz-Zanjani, Mohammad O and Dalsass, Mattia and Farooqee, Sheikh BUD and Lu, Yingzhou and Jackson, Peter K and Van Rechem, Capucine},
  journal={Journal of Biological Chemistry},
  volume={300},
  number={12},
  year={2024},
  publisher={Elsevier}
}

@article{du2024embracing,
  title={Embracing the informative missingness and silent gene in analyzing biologically diverse samples},
  author={Du, Dongping and Bhardwaj, Saurabh and Lu, Yingzhou and Wang, Yizhi and Parker, Sarah J and Zhang, Zhen and Van Eyk, Jennifer E and Yu, Guoqiang and Clarke, Robert and Herrington, David M and others},
  journal={Scientific reports},
  volume={14},
  number={1},
  pages={28265},
  year={2024},
  publisher={Nature Publishing Group UK London}
}


@article{chen2021data,
  title={Data-driven detection of subtype-specific differentially expressed genes},
  author={Chen, Lulu and Lu, Yingzhou and Wu, Chiung-Ting and Clarke, Robert and Yu, Guoqiang and Van Eyk, Jennifer E and Herrington, David M and Wang, Yue},
  journal={Scientific reports},
  volume={11},
  number={1},
  pages={332},
  year={2021},
  publisher={Nature Publishing Group UK London}
}

@article{lu2022cot,
  title={COT: an efficient and accurate method for detecting marker genes among many subtypes},
  author={Lu, Yingzhou and Wu, Chiung-Ting and Parker, Sarah J and Cheng, Zuolin and Saylor, Georgia and Van Eyk, Jennifer E and Yu, Guoqiang and Clarke, Robert and Herrington, David M and Wang, Yue},
  journal={Bioinformatics Advances},
  volume={2},
  number={1},
  pages={vbac037},
  year={2022},
  publisher={Oxford University Press}
}


@article{dan2024image,
  title={Image-driven prediction system: Automatic extraction of aggregate gradation of pavement core samples integrating deep learning and interactive image processing framework},
  author={Dan, Han-Cheng and Huang, Zhetao and Lu, Bingjie and Li, Mengyu},
  journal={Construction and Building Materials},
  volume={453},
  pages={139056},
  year={2024},
  publisher={Elsevier}
}


@article{dan2024evaluation,
  title={Evaluation of asphalt pavement texture using multiview stereo reconstruction based on deep learning},
  author={Dan, Han-Cheng and Lu, Bingjie and Li, Mengyu},
  journal={Construction and Building Materials},
  volume={412},
  pages={134837},
  year={2024},
  publisher={Elsevier}
}


@article{lu2025causalsr,
  title={CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual Inference},
  author={Lu, Zhengyang and Lu, Bingjie and Wang, Feng},
  journal={arXiv preprint arXiv:2501.15852},
  year={2025}
}


@article{lu2025journey,
  title={Journey into Automation: Image-Derived Pavement Texture Extraction and Evaluation},
  author={Lu, Bingjie and Dan, Han-Cheng and Zhang, Yichen and Huang, Zhetao},
  journal={arXiv preprint arXiv:2501.02414},
  year={2025}
}


@article{zhao2023advances,
  title={Advances in NIR-responsive natural macromolecular hydrogel assembly drugs for cancer treatment},
  author={Zhao, Chenyu and Pan, Boyue and Wang, Tianlin and Yang, Huazhe and Vance, David and Li, Xiaojia and Zhao, Haiyang and Hu, Xinru and Yang, Tianchang and Chen, Zihao and others},
  journal={Pharmaceutics},
  volume={15},
  number={12},
  pages={2729},
  year={2023},
  publisher={MDPI}
}


@article{zhao2024antibody,
  title={Antibody-drug conjugates for non-small cell lung cancer: Advantages and challenges in clinical translation},
  author={Zhao, Chenyu and Zhang, Ruihan and Yang, Huazhe and Gao, Yiwei and Zou, Ying and Zhang, Xudong},
  journal={Biochemical Pharmacology},
  pages={116378},
  year={2024},
  publisher={Elsevier}
}


@article{zhao2024acellular,
  title={Acellular fish skin grafts in the treatment of diabetic wounds: Advantages and clinical translation},
  author={Zhao, Chenyu and Feng, Mengyi and Gluchman, Martin and Ma, Xianghe and Li, Jinhao and Wang, Hui},
  journal={Journal of Diabetes},
  volume={16},
  number={5},
  pages={e13554},
  year={2024},
  publisher={Wiley Online Library}
}

@article{zhao2024functional,
  title={Functional biomacromolecules-based microneedle patch for the treatment of diabetic wound},
  author={Zhao, Chenyu and Wu, Zhaoqi and Pan, Boyue and Zhang, Ruihan and Golestani, Avin and Feng, Ziyi and Ge, Yi and Yang, Huazhe},
  journal={International Journal of Biological Macromolecules},
  pages={131650},
  year={2024},
  publisher={Elsevier}
}


@incollection{li2024real,
  title={Real-time idling vehicles detection using combined audio-visual deep learning},
  author={Li, Xiwen and Mangin, Tristalee and Saha, Surojit and Mohammed, Rehman and Blanchard, Evan and Tang, Dillon and Poppe, Henry and Choi, Ouk and Kelly, Kerry and Whitaker, Ross},
  booktitle={Emerging Cutting-Edge Developments in Intelligent Traffic and Transportation Systems},
  pages={142--158},
  year={2024},
  publisher={IOS Press}
}


@inproceedings{li2025joint,
  title={Joint audio-visual idling vehicle detection with streamlined input dependencies},
  author={Li, Xiwen and Mohammed, Rehman and Mangin, Tristalee and Saha, Surojit and Kelly, Kerry and Whitaker, Ross and Tasdizen, Tolga},
  booktitle={Proceedings of the Winter Conference on Applications of Computer Vision},
  pages={885--894},
  year={2025}
}


@article{cdcHIV,
  author = {{Centers for Disease Control and Prevention}},
  title = {HIV Surveillance Report, 2020},
  year = {2022},
  url = {https://www.cdc.gov/mmwr/volumes/71/wr/mm7138a1.htm},
  note = {Accessed: 2025-02-11}
}


@article{chingombe2022predicting,
  title={Predicting HIV status among men who have sex with men in Bulawayo \& Harare, Zimbabwe using bio-behavioural data, recurrent neural networks, and machine learning techniques},
  author={Chingombe, Innocent and Dzinamarira, Tafadzwa and Cuadros, Diego and Mapingure, Munyaradzi Paul and Mbunge, Elliot and Chaputsira, Simbarashe and Madziva, Roda and Chiurunge, Panashe and Samba, Chesterfield and Herrera, Helena and others},
  journal={Tropical Medicine and Infectious Disease},
  volume={7},
  number={9},
  pages={231},
  year={2022},
  publisher={MDPI}
}


@article{nisa2023hiv,
  title={HIV/AIDS predictive model using random forest based on socio-demographical, biological and behavioral data},
  author={Nisa, Sehar Un and Mahmood, Azhar and Ujager, Farhan Sabir and Malik, Mehwish},
  journal={Egyptian Informatics Journal},
  volume={24},
  number={1},
  pages={107--115},
  year={2023},
  publisher={Elsevier}
}


@article{santosh2020covid,
  title={COVID-19 prediction models and unexploited data},
  author={Santosh, KC},
  journal={Journal of medical systems},
  volume={44},
  number={9},
  pages={170},
  year={2020},
  publisher={Springer}
}


@article{wang2019application,
  title={Application of a long short-term memory neural network: a burgeoning method of deep learning in forecasting HIV incidence in Guangxi, China},
  author={Wang, G and Wei, W and Jiang, J and Ning, C and Chen, H and Huang, J and Liang, B and Zang, N and Liao, Y and Chen, R and others},
  journal={Epidemiology \& Infection},
  volume={147},
  pages={e194},
  year={2019},
  publisher={Cambridge University Press}
}

@article{turbe2021deep,
  title={Deep learning of HIV field-based rapid tests},
  author={Turb{\'e}, Val{\'e}rian and Herbst, Carina and Mngomezulu, Thobeka and Meshkinfamfard, Sepehr and Dlamini, Nondumiso and Mhlongo, Thembani and Smit, Theresa and Cherepanova, Valeriia and Shimada, Koki and Budd, Jobie and others},
  journal={Nature medicine},
  volume={27},
  number={7},
  pages={1165--1170},
  year={2021},
  publisher={Nature Publishing Group US New York}
}


@article{bao2021predicting,
  title={Predicting the diagnosis of HIV and sexually transmitted infections among men who have sex with men using machine learning approaches},
  author={Bao, Yining and Medland, Nicholas A and Fairley, Christopher K and Wu, Jinrong and Shang, Xianwen and Chow, Eric PF and Xu, Xianglong and Ge, Zongyuan and Zhuang, Xun and Zhang, Lei},
  journal={Journal of Infection},
  volume={82},
  number={1},
  pages={48--59},
  year={2021},
  publisher={Elsevier}
}


@misc{WHO_HIV_Deaths,
  author    = {{World Health Organization}},
  title     = {HIV/AIDS Key Facts},
  year      = {2024},
  url       = {https://www.who.int/news-room/fact-sheets/detail/hiv-aids},
  note      = {Accessed: February 11, 2025}
}

@misc{CDC_HIV_Diagnoses_2022,
  author       = {{Centers for Disease Control and Prevention}},
  title        = {HIV Diagnoses, Deaths, and Prevalence},
  year         = {2023},
  url          = {https://www.cdc.gov/hiv-data/nhss/hiv-diagnoses-deaths-prevalence.html},
  note         = {Accessed: February 11, 2025}
}

@article{WHO_HIV_AIDS,
  author    = {{World Health Organization}},
  title     = {HIV/AIDS},
  year      = {2024},
  url       = {https://www.who.int/news-room/fact-sheets/detail/hiv-aids},
  note      = {Accessed: February 5, 2025}
}

@misc{who_h1n1_outbreak,
  author       = {{World Health Organization}},
  title        = {Influenza A (H1N1) outbreak},
  year         = {2009},
  url          = {https://www.who.int/emergencies/situations/influenza-a-(h1n1)-outbreak},
  note         = {Accessed: February 7, 2025}
}


@misc{CDCFluStats,
  author = {{Centers for Disease Control and Prevention}},
  title = {Influenza (Flu) Burden in the U.S.},
  year = {2023},
  url = {https://www.cdc.gov/flu-burden/php/about/index.html},
  note = {Accessed: February 7, 2025}
}

@misc{WHOCOVIDDeaths,
  author = {{World Health Organization}},
  title = {WHO Coronavirus (COVID-19) Dashboard: Death Toll},
  year = {2025},
  url = {https://covid19.who.int/},
  note = {Accessed: February 7, 2025}
}


@misc{WHOInfluenza,
  author = {{World Health Organization}},
  title = {Influenza (Seasonal)},
  year = {2023},
  url = {https://www.who.int/news-room/fact-sheets/detail/influenza-(seasonal)},
  note = {Accessed: February 7, 2025}
}

@misc{WHO2020COVID,
  author = {{World Health Organization}},
  title = {Coronavirus disease (COVID-19)},
  year = {2020},
  url = {https://www.who.int/health-topics/coronavirus},
  note = {Accessed: February 7, 2025}
}


@article{allen2016applying,
  title={Applying GIS and machine learning methods to Twitter data for multiscale surveillance of influenza},
  author={Allen, Chris and Tsou, Ming-Hsiang and Aslam, Anoshe and Nagel, Anna and Gawron, Jean-Mark},
  journal={PloS one},
  volume={11},
  number={7},
  pages={e0157734},
  year={2016},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{zhang2017comparative,
  title={A comparative study on predicting influenza outbreaks},
  author={Zhang, Jie and Nawata, Kazumitsu},
  journal={Bioscience trends},
  volume={11},
  number={5},
  pages={533--541},
  year={2017},
  publisher={International Research and Cooperation Association for Bio \& Socio-Sciences~…}
}

@article{owid-coronavirus,
    author = {Edouard Mathieu and Hannah Ritchie and Lucas Rodés-Guirao and Cameron Appel and Daniel Gavrilov and Charlie Giattino and Joe Hasell and Bobbie Macdonald and Saloni Dattani and Diana Beltekian and Esteban Ortiz-Ospina and Max Roser},
    title = {COVID-19 Pandemic},
    journal = {Our World in Data},
    year = {2020},
    note = {https://ourworldindata.org/coronavirus}
}

@article{rothan2020epidemiology,
  title={The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak},
  author={Rothan, Hussin A and Byrareddy, Siddappa N},
  journal={Journal of autoimmunity},
  volume={109},
  pages={102433},
  year={2020},
  publisher={Elsevier}
}

@article{pan2017factors,
  title={Factors associated with HIV testing among participants from substance use disorder treatment programs in the US: A machine learning approach},
  author={Pan, Yue and Liu, Hongmei and Metsch, Lisa R and Feaster, Daniel J},
  journal={AIDS and Behavior},
  volume={21},
  pages={534--546},
  year={2017},
  publisher={Springer}
}

@article{wang2021adolescent,
  title={Adolescent HIV-related behavioural prediction using machine learning: a foundation for precision HIV prevention},
  author={Wang, Bo and Liu, Feifan and Deveaux, Lynette and Ash, Arlene and Gosh, Samiran and Li, Xiaoming and Rundensteiner, Elke and Cottrell, Lesley and Adderley, Richard and Stanton, Bonita},
  journal={Aids},
  volume={35},
  pages={S75--S84},
  year={2021},
  publisher={LWW}
}

@inproceedings{ayachit2020predicting,
  title={Predicting h1n1 and seasonal flu: Vaccine cases using ensemble learning approach},
  author={Ayachit, Sai Sanjay and Kumar, Tanmay and Deshpande, Shriya and Sharma, Nayan and Chaurasia, Kuldeep and Dixit, Mayank},
  booktitle={2020 2nd International Conference on Advances in Computing, Communication Control and Networking (ICACCCN)},
  pages={172--176},
  year={2020},
  organization={IEEE}
}

@inproceedings{inampudi2021machine,
  title={Machine learning based prediction of h1n1 and seasonal flu vaccination},
  author={Inampudi, Srividya and Johnson, Greshma and Jhaveri, Jay and Niranjan, S and Chaurasia, Kuldeep and Dixit, Mayank},
  booktitle={Advanced Computing: 10th International Conference, IACC 2020, Panaji, Goa, India, December 5--6, 2020, Revised Selected Papers, Part I 10},
  pages={139--150},
  year={2021},
  organization={Springer}
}

@article{alessa2019preliminary,
  title={Preliminary flu outbreak prediction using twitter posts classification and linear regression with historical centers for disease control and prevention reports: Prediction framework study},
  author={Alessa, Ali and Faezipour, Miad and others},
  journal={JMIR public health and surveillance},
  volume={5},
  number={2},
  pages={e12383},
  year={2019},
  publisher={JMIR Publications Inc., Toronto, Canada}
}

@article{amin2021early,
  title={Early detection of seasonal outbreaks from twitter data using machine learning approaches},
  author={Amin, Samina and Uddin, Muhammad Irfan and AlSaeed, Duaa H and Khan, Atif and Adnan, Muhammad},
  journal={Complexity},
  volume={2021},
  number={1},
  pages={5520366},
  year={2021},
  publisher={Wiley Online Library}
}

@article{pinter2020covid,
  title={COVID-19 pandemic prediction for Hungary; a hybrid machine learning approach},
  author={Pinter, Gergo and Felde, Imre and Mosavi, Amir and Ghamisi, Pedram and Gloaguen, Richard},
  journal={Mathematics},
  volume={8},
  number={6},
  pages={890},
  year={2020},
  publisher={MDPI}
}

@article{arpaci2021predicting,
  title={Predicting the COVID-19 infection with fourteen clinical features using machine learning classification algorithms},
  author={Arpaci, Ibrahim and Huang, Shigao and Al-Emran, Mostafa and Al-Kabi, Mohammed N and Peng, Minfei},
  journal={Multimedia Tools and Applications},
  volume={80},
  pages={11943--11957},
  year={2021},
  publisher={Springer}
}

@article{dairi2021comparative,
  title={Comparative study of machine learning methods for COVID-19 transmission forecasting},
  author={Dairi, Abdelkader and Harrou, Fouzi and Zeroual, Abdelhafid and Hittawe, Mohamad Mazen and Sun, Ying},
  journal={Journal of biomedical informatics},
  volume={118},
  pages={103791},
  year={2021},
  publisher={Elsevier}
}

@article{moulaei2022comparing,
  title={Comparing machine learning algorithms for predicting COVID-19 mortality},
  author={Moulaei, Khadijeh and Shanbehzadeh, Mostafa and Mohammadi-Taghiabad, Zahra and Kazemi-Arpanahi, Hadi},
  journal={BMC medical informatics and decision making},
  volume={22},
  number={1},
  pages={2},
  year={2022},
  publisher={Springer}
}

@article{ardabili2020covid,
  title={Covid-19 outbreak prediction with machine learning},
  author={Ardabili, Sina F and Mosavi, Amir and Ghamisi, Pedram and Ferdinand, Filip and Varkonyi-Koczy, Annamaria R and Reuter, Uwe and Rabczuk, Timon and Atkinson, Peter M},
  journal={Algorithms},
  volume={13},
  number={10},
  pages={249},
  year={2020},
  publisher={MDPI}
}

@article{khan2020forecast,
  title={Forecast the influenza pandemic using machine learning},
  author={Khan, Muhammad Adnan and Abidi, Wajhe Ul Husnain and Al Ghamdi, Mohammed A and Almotiri, Sultan H and Saqib, Shazia and Alyas, Tahir and Khan, Khalid Masood and Mahmood, Nasir},
  journal={Computers, Materials and Continua},
  volume={66},
  number={1},
  pages={331--340},
  year={2020}
}


%%tb

@article{singh2022evolution,
  title={Evolution of machine learning in tuberculosis diagnosis: a review of deep learning-based medical applications},
  author={Singh, Manisha and Pujar, Gurubasavaraj Veeranna and Kumar, Sethu Arun and Bhagyalalitha, Meduri and Akshatha, Handattu Shankaranarayana and Abuhaija, Belal and Alsoud, Anas Ratib and Abualigah, Laith and Beeraka, Narasimha M and Gandomi, Amir H},
  journal={Electronics},
  volume={11},
  number={17},
  pages={2634},
  year={2022},
  publisher={MDPI}
}

@article{bhirud2017rapid,
  title={Rapid laboratory diagnosis of pulmonary tuberculosis},
  author={Bhirud, Prasanna and Joshi, Ameeta and Hirani, Nilma and Chowdhary, Abhay},
  journal={The International Journal of Mycobacteriology},
  volume={6},
  number={3},
  pages={296--301},
  year={2017},
  publisher={Medknow}
}

@article{rabehi2024improving,
  title={Improving tuberculosis diagnosis and forecasting through machine learning techniques: A systematic review},
  author={Rabehi, Abdelaziz and Kumar, P},
  journal={Metaheuristic Optim. Rev.},
  volume={1},
  number={1},
  pages={35--44},
  year={2024}
}

@article{asada1990potential,
  title={Potential usefulness of an artificial neural network for differential diagnosis of interstitial lung diseases: pilot study.},
  author={Asada, Naoki and Doi, K and MacMahon, H and Montner, SM and Giger, ML and Abe, Ch and Wu, YUZHENG},
  journal={Radiology},
  volume={177},
  number={3},
  pages={857--860},
  year={1990}
}
@inproceedings{veropoulos1998automated,
  title={The automated identification of tubercle bacilli using image processing and neural computing techniques},
  author={Veropoulos, Konstantinos and Campbell, C and Learmonth, G and Knight, B and Simpson, J},
  booktitle={ICANN 98: Proceedings of the 8th International Conference on Artificial Neural Networks, Sk{\"o}vde, Sweden, 2--4 September 1998 8},
  pages={797--802},
  year={1998},
  organization={Springer}
}

@article{el1999predicting,
  title={Predicting active pulmonary tuberculosis using an artificial neural network},
  author={El-Solh, Ali A and Hsiao, Chiu-Bin and Goodnough, Susan and Serghani, Joseph and Grant, Brydon JB},
  journal={Chest},
  volume={116},
  number={4},
  pages={968--973},
  year={1999},
  publisher={Elsevier}
}
%%tb

@article{el1997validity,
  title={Validity of a decision tree for predicting active pulmonary tuberculosis.},
  author={El-Solh, Ali and Mylotte, Joseph and Sherif, Sherif and Serghani, Joseph and Grant, BJ},
  journal={American journal of respiratory and critical care medicine},
  volume={155},
  number={5},
  pages={1711--1716},
  year={1997},
  publisher={American Public Health Association}
}



@article{elveren2011tuberculosis,
  title={Tuberculosis disease diagnosis using artificial neural network trained with genetic algorithm},
  author={Elveren, Erhan and Yumu{\c{s}}ak, Nejat},
  journal={Journal of medical systems},
  volume={35},
  pages={329--332},
  year={2011},
  publisher={Springer}
}

@INPROCEEDINGS{2017dl_detect_tb,
  author={Hooda, Rahul and Sofat, Sanjeev and Kaur, Simranpreet and Mittal, Ajay and Meriaudeau, Fabrice},
  booktitle={2017 IEEE International Conference on Signal and Image Processing Applications (ICSIPA)}, 
  title={Deep-learning: A potential method for tuberculosis detection using chest radiography}, 
  year={2017},
  volume={},
  number={},
  pages={497-502},
  keywords={Feature extraction;Cavity resonators;Machine learning;Lungs;Support vector machines;Diseases;Shape;Deep learning;Tuberculosis;Medical imaging;Chest X-rays},
  doi={10.1109/ICSIPA.2017.8120663}}


@INPROCEEDINGS{tb_deep_nn,
  author={Kant, Sonaal and Srivastava, Muktabh Mayank},
  booktitle={2018 IEEE Symposium Series on Computational Intelligence (SSCI)}, 
  title={Towards Automated Tuberculosis detection using Deep Learning}, 
  year={2018},
  volume={},
  number={},
  pages={1250-1253},
  keywords={Microscopy;Deep learning;Neural networks;Drugs;Immune system;Sensitivity;Computer architecture},
  doi={10.1109/SSCI.2018.8628800}}

@article{hrizi2022tuberculosis,
  title={Tuberculosis disease diagnosis based on an optimized machine learning model},
  author={Hrizi, Olfa and Gasmi, Karim and Ben Ltaifa, Ibtihel and Alshammari, Hamoud and Karamti, Hanen and Krichen, Moez and Ben Ammar, Lassaad and Mahmood, Mahmood A},
  journal={Journal of Healthcare Engineering},
  volume={2022},
  number={1},
  pages={8950243},
  year={2022},
  publisher={Wiley Online Library}
}

@article{hansun2023machine,
  title={Machine and deep learning for tuberculosis detection on chest x-rays: systematic literature review},
  author={Hansun, Seng and Argha, Ahmadreza and Liaw, Siaw-Teng and Celler, Branko G and Marks, Guy B},
  journal={Journal of medical Internet research},
  volume={25},
  pages={e43154},
  year={2023},
  publisher={JMIR Publications Toronto, Canada}
}


@article{ramrakhiani2022optimizing,
  title={Optimizing hepatitis B virus screening in the United States using a simple demographics-based model},
  author={Ramrakhiani, Nathan S and Chen, Vincent L and Le, Michael and Yeo, Yee Hui and Barnett, Scott D and Waljee, Akbar K and Zhu, Ji and Nguyen, Mindie H},
  journal={Hepatology},
  volume={75},
  number={2},
  pages={430--437},
  year={2022},
  publisher={Wiley Online Library}
}

@article{saleem2024hepatitis,
  title={Hepatitis Diagnosis: A Comprehensive Review of Machine Learning Classification Algorithms},
  author={Saleem, Hayveen},
  journal={The Indonesian Journal of Computer Science},
  volume={13},
  number={3},
  year={2024}
}

@article{ali2024harnessing,
  title={Harnessing the potential of artificial intelligence in managing viral hepatitis},
  author={Ali, Guma and Mijwil, Maad M and Adamopoulos, Ioannis and Buruga, Bosco Apparatus and G{\"o}k, Murat and Sallam, Malik},
  journal={Mesopotamian Journal of Big Data},
  volume={2024},
  pages={128--163},
  year={2024}
}

@INPROCEEDINGS{RF_ML,
  author={Bharathi, P T and Bindu, S N and Deepthi, S G and Gunakeerthi, H U and Harshitha, K U},
  booktitle={2024 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES)}, 
  title={AI based solution for Predicting Hepatitis C Virus from Blood Samples}, 
  year={2024},
  volume={},
  number={},
  pages={1-6},
  keywords={Support vector machines;Logistic regression;Accuracy;Liver diseases;Medical services;Feature extraction;Data mining;Hepatitis C Virus;Blood samples;Support Vector Machine;Logistic Regression;Sequential Forward Selection;Decisison Tree;Random Forest;Machine Learning},
  doi={10.1109/ICSSES62373.2024.10561391}}

@article{YAGANOGLU2022102087,
title = {Hepatitis C virus data analysis and prediction using machine learning},
journal = {Data \& Knowledge Engineering},
volume = {142},
pages = {102087},
year = {2022},
issn = {0169-023X},
doi = {https://doi.org/10.1016/j.datak.2022.102087},
url = {https://www.sciencedirect.com/science/article/pii/S0169023X22000787},
author = {Mete Yağanoğlu},
keywords = {Hepatitis C, Machine learning, Data science, Visualization},
abstract = {Medical decision support systems have been on the rise with technological advances and they have been the subject of many studies. Developing an effective medical decision support system requires a high amount of accuracy, precision, and sensitivity as well as time efficiency that is inversely proportional to the complexity of the model. Hepatitis C virus (HCV) infection is one of the most important causes of chronic liver disease worldwide. In this study, data discovery has been made by applying data science processes, and the HCV has been estimated with machine learning methods. By analyzing and visualizing the values in the data set, features that may be important for HCV was determined, and HCV estimation was made using various machine learning methods, pre-processing and feature extraction. According to the features obtained from this study, the estimation of HCV can be made automatically and can be a decision support system that helps the researchers and clinicians. In this study, HCV was obtained with 99.31% accuracy by adding new features and eliminating imbalances between classes. The model in this study can be used as an alternative method in the prediction of Hepatitis C-related diseases.}
}

@article{santangelo2023machine,
  title={Machine learning and prediction of infectious diseases: a systematic review},
  author={Santangelo, Omar Enzo and Gentile, Vito and Pizzo, Stefano and Giordano, Domiziana and Cedrone, Fabrizio},
  journal={Machine Learning and Knowledge Extraction},
  volume={5},
  number={1},
  pages={175--198},
  year={2023},
  publisher={MDPI}
}

@article{baker2022infectious,
  title={Infectious disease in an era of global change},
  author={Baker, Rachel E and Mahmud, Ayesha S and Miller, Ian F and Rajeev, Malavika and Rasambainarivo, Fidisoa and Rice, Benjamin L and Takahashi, Saki and Tatem, Andrew J and Wagner, Caroline E and Wang, Lin-Fa and others},
  journal={Nature reviews microbiology},
  volume={20},
  number={4},
  pages={193--205},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@book{world2022global,
  title={Global report on infection prevention and control},
  author={World Health Organization and others},
  year={2022},
  publisher={World Health Organization},
  address={Geneva}
}

@article{liu2023machine,
  title={Machine learning for infectious disease risk prediction: a survey},
  author={Liu, Mutong and Liu, Yang and Liu, Jiming},
  journal={ACM Computing Surveys},
  year={2023},
  publisher={ACM New York, NY}
}


@article{khabbaz2014challenges,
  title={Challenges of infectious diseases in the USA},
  author={Khabbaz, Rima F and Moseley, Robin R and Steiner, Riley J and Levitt, Alexandra M and Bell, Beth P},
  journal={The Lancet},
  volume={384},
  number={9937},
  pages={53--63},
  year={2014},
  publisher={Elsevier}
}

@article{mishra2022machine,
    author    = {Smriti Mishra and Ranjan Kumar and Sanjay Kumar Tiwari and Priya Ranjan},
    title     = {Machine learning approaches in the diagnosis of infectious diseases: a review},
    journal   = {Bulletin of Electrical Engineering and Informatics},
    volume    = {11},
    number    = {6},
    pages     = {3509--3520},
    year      = {2022},
    doi       = {10.11591/eei.v11i6.4406},
    publisher = {Institute of Advanced Engineering and Science}
}

@article{adams2016summary,
    author    = {Deborah A. Adams},
    title     = {Summary of Notifiable Infectious Diseases and Conditions — United States, 2014},
    journal   = {MMWR. Morbidity and Mortality Weekly Report},
    volume    = {63},
    year      = {2016},
    publisher = {Centers for Disease Control and Prevention (CDC)},
    url       = {https://www.cdc.gov/mmwr/volumes/63/wr/mm6354a1.htm}
}



%%hepatitis

@article{harabor2023machine,
  title={Machine learning approaches for the prediction of hepatitis B and C seropositivity},
  author={Harabor, Valeriu and Mogos, Raluca and Nechita, Aurel and Adam, Ana-Maria and Adam, Gigi and Melinte-Popescu, Alina-Sinziana and Melinte-Popescu, Marian and Stuparu-Cretu, Mariana and Vasilache, Ingrid-Andrada and Mihalceanu, Elena and others},
  journal={International journal of environmental research and public health},
  volume={20},
  number={3},
  pages={2380},
  year={2023},
  publisher={MDPI}
}

@article{wang2020rapid,
  title={Rapid screening of hepatitis B using Raman spectroscopy and long short-term memory neural network},
  author={Wang, Xin and Tian, Shengwei and Yu, Long and Lv, Xiaoyi and Zhang, Zhaoxia},
  journal={Lasers in medical science},
  volume={35},
  number={8},
  pages={1791--1799},
  year={2020},
  publisher={Springer}
}

@article{guo2020prediction,
  title={Prediction of hepatitis E using machine learning models},
  author={Guo, Yanhui and Feng, Yi and Qu, Fuli and Zhang, Li and Yan, Bingyu and Lv, Jingjing},
  journal={Plos one},
  volume={15},
  number={9},
  pages={e0237750},
  year={2020},
  publisher={Public Library of Science San Francisco, CA USA}
}

@ARTICLE{chen_mlp,
  author={Chen, Leran and Ji, Ping and Ma, Yongsheng},
  journal={IEEE Access}, 
  title={Machine Learning Model for Hepatitis C Diagnosis Customized to Each Patient}, 
  year={2022},
  volume={10},
  number={},
  pages={106655-106672},
  keywords={Liver diseases;Machine learning;Data models;Diseases;Computational modeling;Viruses (medical);Modeling;Parameter estimation;Clinical diagnosis;Data augmentation;Machine learning;custom model;hepatitis C;disease diagnosis;data augmentation;parameter optimization},
  doi={10.1109/ACCESS.2022.3210347}
}