{"title":"Ethical Challenges and Current Opportunities of Artificial Intelligence in Cardiology.","authors":"Mohammed A R Chamsi-Pasha, Hassan Chamsi-Pasha","doi":"10.1055/s-0045-1809879","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) has great potential in diagnosing, managing, and predicting cardiovascular diseases through imaging, clinical decision support, remote monitoring, and optimizing treatment strategies. AI in cardiology brings unique ethical issues that need careful examination and resolution. There are several ethical concerns, including privacy, bias, trust, accountability, and responsibility. AI systems handle large quantities of data, which can present privacy and security risks if hacked or exploited illegally. AI models may exhibit biases due to limited or nonrepresentative training data sets, impacting their reliability. ChatGPT shows potential in cardiology for patient education, clinician support, and research facilitation. However, its use in direct patient care is limited due to concerns regarding accuracy, ethical issues, and the necessity for human oversight. AI's responsible development and application in cardiology hinges on thorough evaluation, regulatory compliance, and ethical oversight to ensure safety and effectiveness. The collaboration of health care professionals, data scientists, ethicists, researchers, and policymakers is essential for the advancement of AI in cardiology and the resolution of its associated challenges. Collaboration is mandatory to ensure AI tools improve patient care while upholding the highest medical standards. The incorporation of AI into cardiology offers significant potential for the coming years. With its extensive data sets and strong evidence-based guidelines, cardiology is ideally suited to using this technology.</p>","PeriodicalId":32889,"journal":{"name":"Avicenna Journal of Medicine","volume":"15 3","pages":"95-99"},"PeriodicalIF":0.0000,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12520755/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Avicenna Journal of Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1055/s-0045-1809879","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/7/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) has great potential in diagnosing, managing, and predicting cardiovascular diseases through imaging, clinical decision support, remote monitoring, and optimizing treatment strategies. AI in cardiology brings unique ethical issues that need careful examination and resolution. There are several ethical concerns, including privacy, bias, trust, accountability, and responsibility. AI systems handle large quantities of data, which can present privacy and security risks if hacked or exploited illegally. AI models may exhibit biases due to limited or nonrepresentative training data sets, impacting their reliability. ChatGPT shows potential in cardiology for patient education, clinician support, and research facilitation. However, its use in direct patient care is limited due to concerns regarding accuracy, ethical issues, and the necessity for human oversight. AI's responsible development and application in cardiology hinges on thorough evaluation, regulatory compliance, and ethical oversight to ensure safety and effectiveness. The collaboration of health care professionals, data scientists, ethicists, researchers, and policymakers is essential for the advancement of AI in cardiology and the resolution of its associated challenges. Collaboration is mandatory to ensure AI tools improve patient care while upholding the highest medical standards. The incorporation of AI into cardiology offers significant potential for the coming years. With its extensive data sets and strong evidence-based guidelines, cardiology is ideally suited to using this technology.