Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study.

Abstract excerpt

Background: Serious mental illnesses (SMIs) are associated with high relapse rates and limited access to continuous care, particularly in low-resource settings such as urban slums. Traditional clinical monitoring is constrained by accessibility and scalability challenges. Digital phenotyping, through passive smartphone data, offers a novel approach to predict relapse by capturing real-world behavioral changes....

Topics

Share this publication in a Topic to start or enrich a Post.

• Share to Feasibility Studies
• Share to Mental Disorders