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Adolescent Self-Reflection Process Through Self-Recording on Multiple Health Metrics: Qualitative Study

Adolescent Self-Reflection Process Through Self-Recording on Multiple Health Metrics: Qualitative Study

Between 7 and 9 p.m. is exactly when evening self-study starts, and if I tried hard during that time but things didn’t go well, I’d feel anxious because there’s no time left afterward, and I’ve already let so much time slip by. I realized feeling anxious between 7 and 9 p.m. They would reflect on their behaviors and circumstances surrounding the emotional episodes to gain a deeper understanding of what may have contributed to their emotional distress.

Minseo Cho, Doeun Park, Myounglee Choo, Doug Hyun Han, Jinwoo Kim

J Med Internet Res 2025;27:e62962

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Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

In addition, we analyzed correlations so that we could intuitively examine the relationship between each variable we considered and the outcome. The AUROC, sensitivity, positive predictive value, and accuracy at a threshold were measured to compare the performance of different models. Data processing was performed using Python version 3.6.13. The machine learning model was developed and validated using the Py Caret library version 2.3.10.

Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

J Med Internet Res 2025;27:e59520

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