GPT-4 generated moderate quality information in response to questions regarding sinusitis and surgery. GPT-4 generated significantly higher quality responses to questions regarding treatment of sinusitis. Future studies exploring quality of GPT responses should seek to limit bias and use validated instruments.
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http://dx.doi.org/10.1002/alr.23387 | DOI Listing |
Clin Transl Radiat Oncol
March 2025
Department of Radiation Oncology, Maria Sklodowska-Curie National Research Institute of Oncology, Wawelska 15B, 02-034 Warsaw, Poland.
Background And Purpose: Pediatric radiotherapy patients and their parents are usually aware of their need for radiotherapy early on, but they meet with a radiation oncologist later in their treatment. Consequently, they search for information online, often encountering unreliable sources. Large language models (LLMs) have the potential to serve as an educational pretreatment tool, providing reliable answers to their questions.
View Article and Find Full Text PDFJMIR Med Educ
January 2025
Department of Pharmacy, Taipei Veterans General Hospital Hsinchu Branch, Hsinchu, Taiwan.
Background: OpenAI released versions ChatGPT-3.5 and GPT-4 between 2022 and 2023. GPT-3.
View Article and Find Full Text PDFJ Med Ethics
January 2025
Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA.
Introduction: The integration of artificial intelligence (AI) into healthcare introduces innovative possibilities but raises ethical, legal and professional concerns. Assessing the performance of AI in core components of the United States Medical Licensing Examination (USMLE), such as communication skills, ethics, empathy and professionalism, is crucial. This study evaluates how well ChatGPT versions 3.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
Department of Radiology, Kastamonu University, Kastamonu 37150, Turkey.
The role of artificial intelligence (AI) in radiological image analysis is rapidly evolving. This study evaluates the diagnostic performance of Chat Generative Pre-trained Transformer Omni (GPT-4 Omni) in detecting intracranial hemorrhages (ICHs) in non-contrast computed tomography (NCCT) images, along with its ability to classify hemorrhage type, stage, anatomical location, and associated findings. A retrospective study was conducted using 240 cases, comprising 120 ICH cases and 120 controls with normal findings.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Division of General Internal Medicine, Mayo Clinic College of Medicine and Science, 200 First St SW, Rochester, US.
Background: Virtual patients (VPs) are computer screen-based simulations of patient-clinician encounters. VP use is limited by cost and low scalability.
Objective: Show proof-of-concept that VPs powered by large language models (LLMs) generate authentic dialogs, accurate representations of patient preferences, and personalized feedback on clinical performance; and explore LLMs for rating dialog and feedback quality.
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