{"title":"Inclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.","authors":"Juhi Yasmeen, Md Tauseef Qamar, Subuhi Yasmeen","doi":"10.1016/j.clinimag.2024.110385","DOIUrl":null,"url":null,"abstract":"<p><p>This letter responds to the article \"Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance,\" offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highlights the significance of prompt engineering, we suggest that addressing additional key challenges such as age-related diagnostic needs, socio-economic diversity, data security, and liability concerns is essential for responsible AI integration. Incorporating adaptive prompts, training the model on diverse datasets, and securely integrating it with electronic health records (EHRs) can enhance its reliability and inclusiveness. By balancing prompt design with privacy and accountability frameworks, ChatGPT-4 can become a more effective tool in radiology, aiding clinicians without compromising human oversight.</p>","PeriodicalId":50680,"journal":{"name":"Clinical Imaging","volume":"118 ","pages":"110385"},"PeriodicalIF":1.8000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.clinimag.2024.110385","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/6 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering additional perspectives on optimising ChatGPT-4 for Radiology applications. While the study highlights the significance of prompt engineering, we suggest that addressing additional key challenges such as age-related diagnostic needs, socio-economic diversity, data security, and liability concerns is essential for responsible AI integration. Incorporating adaptive prompts, training the model on diverse datasets, and securely integrating it with electronic health records (EHRs) can enhance its reliability and inclusiveness. By balancing prompt design with privacy and accountability frameworks, ChatGPT-4 can become a more effective tool in radiology, aiding clinicians without compromising human oversight.
期刊介绍：
The mission of Clinical Imaging is to publish, in a timely manner, the very best radiology research from the United States and around the world with special attention to the impact of medical imaging on patient care. The journal''s publications cover all imaging modalities, radiology issues related to patients, policy and practice improvements, and clinically-oriented imaging physics and informatics. The journal is a valuable resource for practicing radiologists, radiologists-in-training and other clinicians with an interest in imaging. Papers are carefully peer-reviewed and selected by our experienced subject editors who are leading experts spanning the range of imaging sub-specialties, which include:
-Body Imaging-
Breast Imaging-
Cardiothoracic Imaging-
Imaging Physics and Informatics-
Molecular Imaging and Nuclear Medicine-
Musculoskeletal and Emergency Imaging-
Neuroradiology-
Practice, Policy & Education-
Pediatric Imaging-
Vascular and Interventional Radiology
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