Clustering Insomnia Patterns by Data From Wearable Devices: Algorithm Development and Validation Study.

Sungkyu Park Sang Won Lee Sungwon Han Meeyoung Cha

Published in: JMIR mHealth and uHealth (2019)

Our research suggests that unsupervised learning allows health practitioners to devise precise and tailored interventions at the level of data-guided user clusters (ie, precision psychiatry), which could be a novel solution to treating insomnia and other mental disorders.

Keyphrases

machine learning
electronic health record
big data
healthcare
public health
primary care
physical activity
mental health
deep learning
single cell
smoking cessation
health information
data analysis
general practice
depressive symptoms