Joy Melnikow, Andrew Padovani, Jingwen Zhang, Marykate Miller, Melissa Gosdin, Sabrina Loureiro, Brock Daniels
Patient concerns and physician strategies for addressing COVID-19 vaccine hesitancy
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background openais chatgpt san francisco ca usa googles gemini mountain view ca usa two large language models show promise improving expediting medical decision making hand surgery evaluating applications models within field hand surgery warranted study aims evaluate chatgpt4 gemini classifying hand injuries recommending treatment methods gemini chatgpt given 68 fictionalized clinical vignettes hand injuries twice models asked use specific classification system recommend surgical nonsurgical treatment classifications scored based correctness results analyzed using descriptive statistics paired twotailed ttest sensitivity testing results gemini correctly classifying 706 hand injuries demonstrated superior classification ability chatgpt mean score 146 vs 087 pvalue 0001 management chatgpt demonstrated higher sensitivity recommending surgical intervention compared gemini 980 vs 888 lower specificity 684 vs 947 compared chatgpt gemini demonstrated greater response replicability conclusions large language models like chatgpt gemini show promise assisting medical decision making particularly hand surgery gemini generally outperforming chatgpt findings emphasize importance considering strengths limitations different models integrating clinical practice