Jonathan Shapiro, Tamar Freud, Baruch Kaplan, Yuval Ramot
{"title":"Exploring the Potential of ChatGPT in Identifying Drug-Drug Interactions in Dermatology.","authors":"Jonathan Shapiro, Tamar Freud, Baruch Kaplan, Yuval Ramot","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Identifying drug-drug interactions (DDIs) in dermatology can be cumbersome and time-consuming using traditional methods.</p><p><strong>Objectives: </strong>To explore the potential of ChatGPT-4o, an artificial intelligence (AI)-based chatbot, to streamline the identification process.</p><p><strong>Methods: </strong>ChatGPT-4o was tasked with assessing DDIs among commonly prescribed dermatological medications. The accuracy and reliability of the chatbot's outputs were compared against established references for 43 interactions.</p><p><strong>Results: </strong>ChatGPT-4o successfully identified all evaluated interactions. It accurately described the interaction effects in 42 cases, with only one example of misdescription.</p><p><strong>Conclusions: </strong>The findings highlight the potential of ChatGPT to serve as an effective and efficient alternative for identifying and understanding DDIs in dermatology, despite one noted error that emphasizes the need for ongoing verification against trusted references. Further research is needed to validate its use across a broader range of medications and clinical scenarios.</p>","PeriodicalId":50268,"journal":{"name":"Israel Medical Association Journal","volume":"27 6","pages":"367-371"},"PeriodicalIF":1.8000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Israel Medical Association Journal","FirstCategoryId":"3","ListUrlMain":"","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Identifying drug-drug interactions (DDIs) in dermatology can be cumbersome and time-consuming using traditional methods.
Objectives: To explore the potential of ChatGPT-4o, an artificial intelligence (AI)-based chatbot, to streamline the identification process.
Methods: ChatGPT-4o was tasked with assessing DDIs among commonly prescribed dermatological medications. The accuracy and reliability of the chatbot's outputs were compared against established references for 43 interactions.
Results: ChatGPT-4o successfully identified all evaluated interactions. It accurately described the interaction effects in 42 cases, with only one example of misdescription.
Conclusions: The findings highlight the potential of ChatGPT to serve as an effective and efficient alternative for identifying and understanding DDIs in dermatology, despite one noted error that emphasizes the need for ongoing verification against trusted references. Further research is needed to validate its use across a broader range of medications and clinical scenarios.
期刊介绍:
The Israel Medical Association Journal (IMAJ), representing medical sciences and medicine in Israel, is published in English by the Israel Medical Association.
The Israel Medical Association Journal (IMAJ) was initiated in 1999.