Late fusion of machine learning models using passively captured interpersonal social interactions and motion from smartphones predicts decompensation in heart failure

• Main Authors: Cakmak, Ayse S, Densen, Samuel, Najarro, Gabriel, Rout, Pratik, Rozell, Christopher J, Inan, Omer T, Shah, Amit J, Clifford, Gari D
• Format: Journal Article
• Language: English
• Published: 03.04.2021
• Subjects: Computer Science - Learning
• DOI: 10.48550/arxiv.2104.01511

Objective: Worldwide, heart failure (HF) is a major cause of morbidity and mortality and one of the leading causes of hospitalization. Early detection of HF symptoms and pro-active management may reduce adverse events. Approach: Twenty-eight participants were monitored using a smartphone app after d...