{"title":"自动化、自然语言处理、人工智能和机器学习在医院环境中识别和预防药物不良反应的作用","authors":"Akanksha Togra, S. Pawar","doi":"10.53411/jpadr.2022.3.3.02","DOIUrl":null,"url":null,"abstract":"Patient Safety is at the center of all pharmacovigilance activities. As several covariates can impact the safety of a medicinal product in patients, a large amount of data is required for an accurate assessment of the safety and therefore, the benefit-risk balance of a medicinal product. Natural language processing, Artificial Intelligence, and Machine Learning are being popularly used to facilitate various pharmacovigilance activities in the Pharma industry. Artificial Intelligence and Machine learning if properly used in hospital settings can also facilitate the identification of adverse events from hospital records and discharge summaries and prescription errors, thus, alerting treating physicians regarding the same. However, the potential of using these techniques needs to be fully explored in hospital settings to facilitate the collection and evaluation of safety data.","PeriodicalId":388338,"journal":{"name":"Journal of Pharmacovigilance and Drug Research","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Role of Automation, Natural Language Processing, Artificial Intelligence, and Machine Learning in hospital settings to identify and prevent Adverse Drug Reactions\",\"authors\":\"Akanksha Togra, S. Pawar\",\"doi\":\"10.53411/jpadr.2022.3.3.02\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Patient Safety is at the center of all pharmacovigilance activities. As several covariates can impact the safety of a medicinal product in patients, a large amount of data is required for an accurate assessment of the safety and therefore, the benefit-risk balance of a medicinal product. Natural language processing, Artificial Intelligence, and Machine Learning are being popularly used to facilitate various pharmacovigilance activities in the Pharma industry. Artificial Intelligence and Machine learning if properly used in hospital settings can also facilitate the identification of adverse events from hospital records and discharge summaries and prescription errors, thus, alerting treating physicians regarding the same. However, the potential of using these techniques needs to be fully explored in hospital settings to facilitate the collection and evaluation of safety data.\",\"PeriodicalId\":388338,\"journal\":{\"name\":\"Journal of Pharmacovigilance and Drug Research\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Pharmacovigilance and Drug Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.53411/jpadr.2022.3.3.02\",\"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 Pharmacovigilance and Drug Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53411/jpadr.2022.3.3.02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Role of Automation, Natural Language Processing, Artificial Intelligence, and Machine Learning in hospital settings to identify and prevent Adverse Drug Reactions
Patient Safety is at the center of all pharmacovigilance activities. As several covariates can impact the safety of a medicinal product in patients, a large amount of data is required for an accurate assessment of the safety and therefore, the benefit-risk balance of a medicinal product. Natural language processing, Artificial Intelligence, and Machine Learning are being popularly used to facilitate various pharmacovigilance activities in the Pharma industry. Artificial Intelligence and Machine learning if properly used in hospital settings can also facilitate the identification of adverse events from hospital records and discharge summaries and prescription errors, thus, alerting treating physicians regarding the same. However, the potential of using these techniques needs to be fully explored in hospital settings to facilitate the collection and evaluation of safety data.