Version 1
: Received: 18 August 2023 / Approved: 22 August 2023 / Online: 22 August 2023 (08:29:03 CEST)
Version 2
: Received: 22 September 2023 / Approved: 25 September 2023 / Online: 25 September 2023 (05:19:01 CEST)
How to cite:
Devi, V. R.; Keidar, M. Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and AI Techniques. Preprints2023, 2023081539. https://doi.org/10.20944/preprints202308.1539.v2
Devi, V. R.; Keidar, M. Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and AI Techniques. Preprints 2023, 2023081539. https://doi.org/10.20944/preprints202308.1539.v2
Devi, V. R.; Keidar, M. Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and AI Techniques. Preprints2023, 2023081539. https://doi.org/10.20944/preprints202308.1539.v2
APA Style
Devi, V. R., & Keidar, M. (2023). Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and AI Techniques. Preprints. https://doi.org/10.20944/preprints202308.1539.v2
Chicago/Turabian Style
Devi, V. R. and Michael Keidar. 2023 "Personalized Plasma Medicine for Cancer: Transforming Treatment Strategies with Mathematical Modeling and AI Techniques" Preprints. https://doi.org/10.20944/preprints202308.1539.v2
Abstract
Plasma technology shows tremendous potential for revolutionizing oncology research and treatment. Reactive oxygen and nitrogen species, electromagnetic emissions generated through gas plasma jets, have attracted significant attention due to their selective cytotoxicity towards cancer cells. To leverage the full potential of plasma medicine, researchers have explored the use of mathematical models and various subsets of machine learning, such as reinforcement learning, and deep learning. This review emphasizes the significant application of AI algorithms in the adaptive plasma system, paving the way for precision and dynamic cancer treatment. Realizing the full potential of AI in plasma medicine, requires research efforts, data sharing and interdisciplinary collaborations. Unravelling the complex mechanisms, developing real-time diagnostics, and optimizing AI models will be crucial to harness the true power of plasma technology in oncology. The integration of personalized and dynamic plasma therapies, alongside AI and diagnostic sensors, presents a transformative approach to cancer treatment with the potential to improve outcomes globally.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Commenter: Viswambari Devi
Commenter's Conflict of Interests: Author