Evaluating Recommendations About Atrial Fibrillation for Patients and Clinicians Obtained From Chat-Based Artificial Intelligence Algorithms

HomeCirculation: Arrhythmia and ElectrophysiologyVol. 16, No. 7Evaluating Recommendations About Atrial Fibrillation for Patients and Clinicians Obtained From Chat-Based Artificial Intelligence Algorithms No AccessResearch ArticleRequest AccessFull TextAboutView Full TextView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toNo AccessResearch ArticleRequest AccessFull TextEvaluating Recommendations About Atrial Fibrillation for Patients and Clinicians Obtained From Chat-Based Artificial Intelligence Algorithms Zahra Azizi, Pouria Alipour, Sofia Gomez, Cassandra Broadwin, Sumaiya Islam, Ashish Sarraju, A.J. Rogers, Alexander T. Sandhu and Fatima Rodriguez Zahra AziziZahra Azizi https://orcid.org/0000-0002-7897-0934 Center for Digital Health (Z.A., C.B., S.I.). Search for more papers by this author , Pouria AlipourPouria Alipour https://orcid.org/0000-0002-0751-2995 Department of Medicine, McGill University, Montreal, QC, Canada (P.A.). Search for more papers by this author , Sofia GomezSofia Gomez Department of Medicine, Stanford School of Medicine, CA (S.G.). Search for more papers by this author , Cassandra BroadwinCassandra Broadwin Center for Digital Health (Z.A., C.B., S.I.). Search for more papers by this author , Sumaiya IslamSumaiya Islam https://orcid.org/0000-0001-6901-9883 Center for Digital Health (Z.A., C.B., S.I.). Search for more papers by this author , Ashish SarrajuAshish Sarraju https://orcid.org/0000-0003-1649-2110 Department of Cardiovascular Medicine, Cleveland Clinic, OH (A.S.). Search for more papers by this author , A.J. RogersA.J. Rogers https://orcid.org/0000-0001-6585-534X Stanford University Division of Cardiovascular Medicine & Cardiovascular Institute, Department of Medicine, Stanford University, CA (A.J.R., A.T.S., F.R.). Search for more papers by this author , Alexander T. SandhuAlexander T. Sandhu https://orcid.org/0000-0003-3208-1143 Stanford University Division of Cardiovascular Medicine & Cardiovascular Institute, Department of Medicine, Stanford University, CA (A.J.R., A.T.S., F.R.). Department of Cardiovascular Medicine, Cleveland Clinic, OH (A.S.). Search for more papers by this author and Fatima RodriguezFatima Rodriguez Correspondence to: Fatima Rodriguez, MD, MPH, Division of Cardiovascular Medicine, Stanford University, Mail Code 5687, 453 Quarry Rd, Center for Academic Medicine, Stanford, CA 94304. Email E-mail Address: [email protected] https://orcid.org/0000-0002-5226-0723 Stanford University Division of Cardiovascular Medicine & Cardiovascular Institute, Department of Medicine, Stanford University, CA (A.J.R., A.T.S., F.R.). Search for more papers by this author Originally published19 Jun 2023https://doi.org/10.1161/CIRCEP.123.012015Circulation: Arrhythmia and Electrophysiology. 2023;16:415–417FootnotesThis article was sent to Andrew E. Epstein, MD, Guest Editor, for review by expert referees, editorial decision, and final disposition.For Sources of Funding and Disclosures, see page 416.Correspondence to: Fatima Rodriguez, MD, MPH, Division of Cardiovascular Medicine, Stanford University, Mail Code 5687, 453 Quarry Rd, Center for Academic Medicine, Stanford, CA 94304. Email [email protected].eduReferences1. Wilson RE, Rush KL. Engaging Patients in Atrial Fibrillation Self-Care: Opportunities for Future Research. In: Los Angeles, CA: SAGE Publications Sage CA; 2021:1091–1092.Google Scholar2. Palm P, Qvist I, Rasmussen TB, Christensen SW, Håkonsen SJ, Risom SS. Educational interventions to improve outcomes in patients with atrial fibrillation—a systematic review.Int J Clin Pract. 2020; 74:e13629. doi: 10.1111/ijcp.13629CrossrefMedlineGoogle Scholar3. Mann DL. Artificial intelligence discusses the role of artificial intelligence in translational medicine.JACC Basic Transl Sci. 2023; 8:221–223. doi: 10.1016/j.jacbts.2023.01.001CrossrefMedlineGoogle Scholar4. Sarraju A, Bruemmer D, Van Iterson E, Cho L, Rodriguez F, Laffin L. Appropriateness of cardiovascular disease prevention recommendations obtained from a popular online chat-based artificial intelligence model.JAMA. 2023; 329:842–844. doi: 10.1001/jama.2023.1044CrossrefMedlineGoogle Scholar5. Alkaissi H, McFarlane SI. Artificial hallucinations in ChatGPT: implications in scientific writing.Cureus. 2023; 15:e35179. doi: 10.7759/cureus.35179CrossrefMedlineGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails July 2023Vol 16, Issue 7 Advertisement Article InformationMetrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/CIRCEP.123.012015PMID: 37334705 Originally publishedJune 19, 2023 Keywordsatrial fibrillationarrhythmiaphysicianspatientsPDF download Advertisement SubjectsAtrial FibrillationMachine Learning and Artificial Intelligence