Modeling the efficacy of different anti-angiogenic drugs on treatment of solid tumors using 3D computational modeling and machine learning
Mousavi Milad; Manshadi Mahsa Dehghan; Soltani Madjid; Kashkooli Farshad M.; Rahmim Arman; Mosavi Amir; Kvasnica Michal; Atkinson Peter M.; Kovács Levente; Koltay Andras; Kis Norbert; Adeli Hojjat
MTMT : 32792285
Date : 2022
Journal title : Computers in Biology and Medicine
Journal volume : 2022
Pages : 1-35
Document type : folyóiratcikk
Subject : solid tumor, tumor growth, anti-angiogenic drugs, bevacizumab, ranibizumab, brolucizumab, artificial intelligence, cancer, Orvostudományok, Elméleti orvostudományok
Abstract :
Conclusion: We demonstrated that SVM combined with genetic optimization algorithm could be lead to more accuracy. Therefore, our study confirms that the GSVMA method outperforms other methods so that it can facilitate CAD diagnosis.