{"title":"机器学习在药物设计和交付中的作用","authors":"Jonathan P. Bernick","doi":"10.4172/2329-6631.1000E143","DOIUrl":null,"url":null,"abstract":"The applications discussed in this article typically use learning machines to perform supervised classification; i.e., the construction of algorithms to determine of the presence or absence of an exemplar in a class based on the values of the data comprising said exemplar. For example, a pharmacologist who wished to predict whether potential drug compounds were neurotoxic or not might use machine learning to construct a decision function from a set of drugs of known neurotoxicity or lack-thereof, and the function thus created would classify other drug compounds as belonging to the mutually exclusive classes of “neurotoxic” or “non-neurotoxic.”","PeriodicalId":15589,"journal":{"name":"Journal of Developing Drugs","volume":"84 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2015-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"The Role of Machine Learning in Drug Design and Delivery\",\"authors\":\"Jonathan P. Bernick\",\"doi\":\"10.4172/2329-6631.1000E143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The applications discussed in this article typically use learning machines to perform supervised classification; i.e., the construction of algorithms to determine of the presence or absence of an exemplar in a class based on the values of the data comprising said exemplar. For example, a pharmacologist who wished to predict whether potential drug compounds were neurotoxic or not might use machine learning to construct a decision function from a set of drugs of known neurotoxicity or lack-thereof, and the function thus created would classify other drug compounds as belonging to the mutually exclusive classes of “neurotoxic” or “non-neurotoxic.”\",\"PeriodicalId\":15589,\"journal\":{\"name\":\"Journal of Developing Drugs\",\"volume\":\"84 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Developing Drugs\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4172/2329-6631.1000E143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Developing Drugs","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/2329-6631.1000E143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Role of Machine Learning in Drug Design and Delivery
The applications discussed in this article typically use learning machines to perform supervised classification; i.e., the construction of algorithms to determine of the presence or absence of an exemplar in a class based on the values of the data comprising said exemplar. For example, a pharmacologist who wished to predict whether potential drug compounds were neurotoxic or not might use machine learning to construct a decision function from a set of drugs of known neurotoxicity or lack-thereof, and the function thus created would classify other drug compounds as belonging to the mutually exclusive classes of “neurotoxic” or “non-neurotoxic.”