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The performance of ChatGPT versus neurosurgery residents in neurosurgical board examination-like questions: a systematic review and meta-analysis.
Neurosurg Rev
December 2024
Division of Neurosurgery, Department of Neurosciences, College of Medicine and Philippine General Hospital, University of the Philippines Manila, Manila, Philippines.
Objective: Large language models and ChatGPT have been used in different fields of medical education. This study aimed to review the literature on the performance of ChatGPT in neurosurgery board examination-like questions compared to neurosurgery residents.
Methods: A literature search was performed following PRISMA guidelines, covering the time period of ChatGPT's inception (November 2022) until October 25, 2024.
Exploring ChatGPT's potential in ECG interpretation and outcome prediction in emergency department.
Am J Emerg Med
November 2024
Department of Internal Medicine, Intermediate Care Unit, Hospital Alto Vicentino (AULSS-7), Santorso, Italy.
Background: Approximately 20 % of emergency department (ED) visits involve cardiovascular symptoms. While ECGs are crucial for diagnosing serious conditions, interpretation accuracy varies among emergency physicians. Artificial intelligence (AI), such as ChatGPT, could assist in ECG interpretation by enhancing diagnostic precision.
View Article and Find Full Text PDFThe aim of this scoping review is to shed light on the current state of the art regarding ChatGPT's potential applications in clinical decision support, as well as its accuracy, sensitivity, speed, and reliability in different clinical contexts (diagnosis, differential diagnosis, treatment, triage, surgical support). Most of the articles found were original research articles, with a few reviews and commentaries. A total of 225 articles were found, of which 50 were included based on retrieval and eligibility.
View Article and Find Full Text PDFHarnessing the Power of ChatGPT in Cardiovascular Medicine: Innovations, Challenges, and Future Directions.
J Clin Med
October 2024
Department of Cardiothoracic Surgery, Stanford University School of Medicine, 300 Pasteur Drive, Falk CVRB, Stanford, CA 94305, USA.
Cardiovascular diseases remain the leading cause of morbidity and mortality globally, posing significant challenges to public health. The rapid evolution of artificial intelligence (AI), particularly with large language models such as ChatGPT, has introduced transformative possibilities in cardiovascular medicine. This review examines ChatGPT's broad applications in enhancing clinical decision-making-covering symptom analysis, risk assessment, and differential diagnosis; advancing medical education for both healthcare professionals and patients; and supporting research and academic communication.
View Article and Find Full Text PDFAssessing the need for coronary angiography in high-risk non-ST-elevation acute coronary syndrome patients using artificial intelligence and computed tomography.
Int J Cardiovasc Imaging
November 2024
Cardiology Department, University Hospital of Lausanne and University of Lausanne, Rue de Bugnon 46, Lausanne, 1011, Switzerland.
Article Synopsis
- The study assessed how well ChatGPT can help decide if high-risk non-ST-elevation acute coronary syndrome (NSTE-ACS) patients need invasive coronary angiography (ICA) based on clinical data and imaging findings.
- In a trial involving 86 patients, ChatGPT showed high accuracy at 86%, correctly advising against ICA for 19 patients and recommending it for 67, leading to significant findings in most cases.
- The results indicate ChatGPT could aid in decision-making to avoid unnecessary procedures, but more extensive studies are needed to truly evaluate AI's effectiveness in clinical settings.
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