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Performance of Plug-In Augmented ChatGPT and Its Ability to Quantify Uncertainty: Simulation Study on the German Medical Board Examination

Performance of Plug-In Augmented ChatGPT and Its Ability to Quantify Uncertainty: Simulation Study on the German Medical Board Examination

Uncertainty calculations displayed as 95% CIs were computed via bootstrapping [18]. Characteristics of GPT model answers (N=541). a N/A: not applicable. The primary outcome was determined by comparing the performance of the GPT-4 model, integrated with the plugins and the English translation, to the required passing score for the medical board examination, which is 60%. The difference of proportions was calculated with 95% CI using bootstrapping (Multimedia Appendix 4).

Julian Madrid, Philipp Diehl, Mischa Selig, Bernd Rolauffs, Felix Patricius Hans, Hans-Jörg Busch, Tobias Scheef, Leo Benning

JMIR Med Educ 2025;11:e58375

A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study

A Comparison of Different Modeling Techniques in Predicting Mortality With the Tilburg Frailty Indicator: Longitudinal Study

We applied each modeling technique, as mentioned in the Modeling Techniques section, to the data set mentioned in the Measures section and validated the models with bootstrapping (100 repetitions) as described in the Analysis section. Table 2 presents the performance characteristics of the models. The corrected AUROC values varied from 0.605 for RP to 0.812 for NN. The optimism of the NN model was high (0.156).

Tjeerd van der Ploeg, Robbert Gobbens

JMIR Med Inform 2022;10(3):e31480