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Artificial Intelligence-Driven Biological Age Prediction Model Using Comprehensive Health Checkup Data: Development and Validation Study

Artificial Intelligence-Driven Biological Age Prediction Model Using Comprehensive Health Checkup Data: Development and Validation Study

SHAP summary plots for the model from the gradient boosting model (A) and the support vector machine (SVM) model (B) are visualized. Features with broader spreads and higher SHAP values have a more significant impact to predict biological age and values with the color gradient indicate whether higher or lower feature values are associated with increased biological age predictions.

Chang-Uk Jeong, Jacob S Leiby, Dokyoon Kim, Eun Kyung Choe

JMIR Aging 2025;8:e64473

Assessing the Cultural Fit of a Digital Sleep Intervention for Refugees in Germany: Qualitative Study

Assessing the Cultural Fit of a Digital Sleep Intervention for Refugees in Germany: Qualitative Study

Frequency analyses of positive and negative feedback given by the refugees from (A) Ukraine and (B) other countries of origin participating in the qualitative study in Germany. The numbers of positive and negative feedback are illustrated separately for the adapted version and the nonadapted version of the digital intervention Sleep-e tested in the study. oth: other countries of origin; ukr: Ukraine. You can take a lot from it also. And you can learn easily also. To have the training..., it’s much easier.

Maja Blomenkamp, Andrea Kiesel, Harald Baumeister, Dirk Lehr, Josef Unterrainer, Lasse B Sander, Kerstin Spanhel

JMIR Form Res 2025;9:e65412