Prediction

The goal of this observational study is to learn about the ability of a point risk score prediction model, developed using electronic medical record data, to predict the risk of progression from geriatric depression to dementia in older Chinese adults. The main questions it aims to answer are: Does a higher point risk score increase the risk of developing dementia in older adults with depression? What is the accuracy of the point risk score prediction model in identifying individuals at high risk of dementia among older adults with depression? Participants will receive their usual medical care as they normally would. No new treatments, tests, or procedures will be performed specifically for this study. The research team will collect data from their electronic medical records, including depression diagnoses, dementia diagnoses, comorbidities, medication records, and follow-up information. The point risk score will be calculated based on these routinely collected clinical data.

This study aims to evaluate the accuracy of temperature change (ΔT) measurements using infrared thermography to predict a successful erector spinae plane block in pediatric patients undergoing inguinal hernia repair under general anesthesia.

This project intends to track and evaluate whether post-ICU syndrome will occur 7 days, 1 month, 3 months and 6 months after ICU patients are transferred out of the ICU through a longitudinal study, apply the latent category growth model to identify different trajectory patterns of post-ICU syndrome in critically ill patients, and use modern machine learning models to build an early warning model of the trajectory patterns of post-ICU syndrome.