{"title":"Aspect-Level Drug Reviews Sentiment Analysis and COVID-19 Drug prediction using PPI & Deep Learning","authors":"Rohit Shivdas Jayale, S. Desai","doi":"10.1109/CCGE50943.2021.9776369","DOIUrl":null,"url":null,"abstract":"The immense pressure and tension has created in the worldwide healthcare systems by disease. Various existing system has defined drug prediction system based on current patient evaluation. In this research we proposed a drug prediction for COVID-19 patient based on protein to protein reactions and availability. In order to evaluate the protein-protein interactions (PPIs) between some of the virus and individual receptors that are also confirmed utilizing biomedical simulations, the framework also defines machine learning models. The classification techniques are consistent with the predictions of separate physical material sequence-based characteristics such as classification of amino acids, distribution of pseudo amino acids and conjoint triads. Finally we will evaluate the system with numerous machine learning algorithm and show the effectiveness of propose systems.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGE50943.2021.9776369","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The immense pressure and tension has created in the worldwide healthcare systems by disease. Various existing system has defined drug prediction system based on current patient evaluation. In this research we proposed a drug prediction for COVID-19 patient based on protein to protein reactions and availability. In order to evaluate the protein-protein interactions (PPIs) between some of the virus and individual receptors that are also confirmed utilizing biomedical simulations, the framework also defines machine learning models. The classification techniques are consistent with the predictions of separate physical material sequence-based characteristics such as classification of amino acids, distribution of pseudo amino acids and conjoint triads. Finally we will evaluate the system with numerous machine learning algorithm and show the effectiveness of propose systems.