Version 1
: Received: 16 October 2023 / Approved: 18 October 2023 / Online: 19 October 2023 (03:54:57 CEST)
How to cite:
Faghihi, U.; Kalantarpour, C.; Baldé, I.; Saki, A. Causal Fuzzy Deep Learning Algorithm for the Differentiation of Gliosarcoma From Glioblastoma. Preprints2023, 2023101190. https://doi.org/10.20944/preprints202310.1190.v1
Faghihi, U.; Kalantarpour, C.; Baldé, I.; Saki, A. Causal Fuzzy Deep Learning Algorithm for the Differentiation of Gliosarcoma From Glioblastoma. Preprints 2023, 2023101190. https://doi.org/10.20944/preprints202310.1190.v1
Faghihi, U.; Kalantarpour, C.; Baldé, I.; Saki, A. Causal Fuzzy Deep Learning Algorithm for the Differentiation of Gliosarcoma From Glioblastoma. Preprints2023, 2023101190. https://doi.org/10.20944/preprints202310.1190.v1
APA Style
Faghihi, U., Kalantarpour, C., Baldé, I., & Saki, A. (2023). Causal Fuzzy Deep Learning Algorithm for the Differentiation of Gliosarcoma From Glioblastoma. Preprints. https://doi.org/10.20944/preprints202310.1190.v1
Chicago/Turabian Style
Faghihi, U., Ismaila Baldé and Amir Saki. 2023 "Causal Fuzzy Deep Learning Algorithm for the Differentiation of Gliosarcoma From Glioblastoma" Preprints. https://doi.org/10.20944/preprints202310.1190.v1
Abstract
In this paper, we introduce an innovative approach to distinguish Gliosarcoma (GSM) from Glioblastoma (GBM). Our method combines causal fuzzy logic rules with the Big Bird architecture, a Transformer-based Deep Learning algorithm. Unlike prior research, which often relied on statistical models to reduce dataset dimensions before causal analysis, our approach harnesses the complete dataset in tandem with our causal fuzzy Big Bird architecture. Additionally, we benchmark our results not only against previous Gliosarcoma/Glioblastoma studies but also against GPT-2 for a comprehensive evaluation.
Keywords
Cancer ; Gliosarcoma; fuzzy logic; deep Learning algorithms; GPT
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
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.
