Siva Prasad Pinnamaneni, G. K. tej, D. Kartheek, B. Dayamani, Ch. Geya, A. Surendra
{"title":"Drug Combination Therapy for Malaria using Deep Learning","authors":"Siva Prasad Pinnamaneni, G. K. tej, D. Kartheek, B. Dayamani, Ch. Geya, A. Surendra","doi":"10.48047/ijfans/v11/i12/192","DOIUrl":null,"url":null,"abstract":"Drug Combination has been effective for treating complex disorders like cancer and infectious diseases. Malaria remains a major global health challenge, with millions of cases and hundreds of thousands of deaths reported annually. While several drugs are available for malaria treatment, drug resistance has emerged as a significant problem. Combination therapy is now recommended as the first-line treatment for malaria. Due to the impossibility and high cost of considering every possible drug combination, it is necessary to put a lot of work into screening new drug combinations. Recently, deep learning techniques have shown promising results in discovering synergistic combinations. We present synergistic drug combinations for malaria and compare and analyze various models that predict effective drug combinations using deep learning techniques","PeriodicalId":290296,"journal":{"name":"International Journal of Food and Nutritional Sciences","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Food and Nutritional Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48047/ijfans/v11/i12/192","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Drug Combination has been effective for treating complex disorders like cancer and infectious diseases. Malaria remains a major global health challenge, with millions of cases and hundreds of thousands of deaths reported annually. While several drugs are available for malaria treatment, drug resistance has emerged as a significant problem. Combination therapy is now recommended as the first-line treatment for malaria. Due to the impossibility and high cost of considering every possible drug combination, it is necessary to put a lot of work into screening new drug combinations. Recently, deep learning techniques have shown promising results in discovering synergistic combinations. We present synergistic drug combinations for malaria and compare and analyze various models that predict effective drug combinations using deep learning techniques