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Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases

Evaluating the Diagnostic Performance of Large Language Models on Complex Multimodal Medical Cases

However, their proficiency in real-world medical reasoning, especially when integrating multimodal data remains uncertain [2]. This study evaluates the ability of 3 commonly used LLMs—Google Bard (subsequently rebranded Gemini), Claude 2, and GPT-4—to generate differential diagnoses (ddx) from complex multimodality diagnostic cases. Consecutive case records of the Massachusetts General Hospital from July 2020 to June 2023 were selected [3].

Wan Hang Keith Chiu, Wei Sum Koel Ko, William Chi Shing Cho, Sin Yu Joanne Hui, Wing Chi Lawrence Chan, Michael D Kuo

J Med Internet Res 2024;26:e53724

Instructional Video and Medical Student Surgical Knot-Tying Proficiency: Randomized Controlled Trial

Instructional Video and Medical Student Surgical Knot-Tying Proficiency: Randomized Controlled Trial

Following a 4-hour preclinical training course, the students reported increased confidence and proficiency and lowered levels of anxiety. Focused surgical skills electives have also been implemented to help prepare senior medical students for entering residency [6-8]. There is no standardized method of teaching medical students knot-tying skills and several curricula have been proposed [9-11].

Katarzyna Bochenska, Magdy P Milad, John OL DeLancey, Christina Lewicky-Gaupp

JMIR Med Educ 2018;4(1):e9