https://www.selleckchem.com/products/bi-2493.html
Objective We aimed to develop a machine learning algorithm to screen for depression and assess severity based on data from wearable devices. Methods We used a wearable device that calculates steps, energy expenditure, body movement, sleep time, heart rate, skin temperature, and ultraviolet light exposure. Depressed patients and healthy volunteers wore the device continuously for the study period. The modalities were compared hourly between patients and healthy volunteers. XGBoost was used to build machine learning models and 10-fold cro
Aimer
Commentaire
Partagez
