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Performance Evaluation and Implications of Large Language Models in Radiology Board Exams: Prospective Comparative Analysis.
JMIR Med Educ
January 2025
Department of Ultrasound, Peking University First Hospital, 8 Xishiku Rd, Xicheng District, Beijing, 100034, China, 86 13132150190, 86 314521.
Background: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.
Objective: This study evaluates the performance of mainstream large language models, including GPT-4, Claude, Bard, Tongyi Qianwen, and Gemini Pro, in radiology board exams.
Methods: A comparative analysis of 150 multiple-choice questions from radiology board exams without images was conducted.
Nonacademic predictors of China medical licensing examination.
BMC Med Educ
January 2025
Department of Radiology and Tianjin Key Lab of Functional Imaging and Tianjin Institute of Radiology and State Key Laboratory of Experimental Hematology, Tianjin Medical University General Hospital, Tianjin, 300052, China.
Background: National Medical Licensing Examination (NMLE) is the entrance exam for medical practice in China, and its general medical knowledge test (GMKT) evaluates abilities of medical students to comprehensively apply medical knowledge to clinical practice. This study aimed to identify nonacademic predictors of GMKT performance, which would benefit medical schools in designing appropriate strategies and techniques to facilitate the transition from medical students to qualified medical practitioners.
Methods: In 1202 medical students, we conducted the deletion-substitution-addition (DSA) and structural equation model (SEM) analyses to identify nonacademic predictors of GMKT performance from 98 candidate variables including early life events, physical conditions, psychological and personality assessments, cognitive abilities, and socioeconomic conditions.
Continuing Education Certificate in Trauma Skills Among Emergency Nurses: A National Sample Survey Analysis.
J Trauma Nurs
January 2025
Author Affiliations: Castner Incorporated, Grand Island, NY (Dr Castner); Health Policy, Management, and Behavior, School of Public Health, University at Albany, Albany, New York (Dr Castner); Stony Brook University School of Nursing, Stony Brook, NY (Ms Zazzera); and Nursing Research and Evidence-Based Practice, Penn Medicine Lancaster General Health, Lancaster, PA (Dr Burchill).
Background: Trauma population health indicators are worsening in the United States. Nurses working in trauma care settings require specialized training for patient care. Little is known about national enumeration of nurses who hold skill-based trauma certificates.
View Article and Find Full Text PDFDirect-to-consumer semen analysis products: Content, accountability, and adherence to clinical guidelines.
Andrology
January 2025
Department of Urology, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Background: Direct-to-consumer (DTC) semen analysis (SA) products obviate barriers that deter men from clinic testing and have made strides in providing higher quality data. However, it is unclear how well these products adhere to the 2021 WHO guidelines on examination and processing of human spermatozoa as they pertain to the evaluation of male fertility.
Objective: We investigate the content and adherence to clinical guidelines associated with consumer-facing information on DTC analysis products.
Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study.
JMIR Med Inform
January 2025
Department of Science and Education, Shenzhen Baoan Women's and Children's Hospital, Shenzhen, China.
Background: Large language models (LLMs) have been proposed as valuable tools in medical education and practice. The Chinese National Nursing Licensing Examination (CNNLE) presents unique challenges for LLMs due to its requirement for both deep domain-specific nursing knowledge and the ability to make complex clinical decisions, which differentiates it from more general medical examinations. However, their potential application in the CNNLE remains unexplored.
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