Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling.

Tahsin Mullick Sam Shaaban Ana Radovic Afsaneh Doryab

Published in: JMIR AI (2024)

The FLMS aims to fill the gap that currently exists when modeling passive sensor data with a small number of data points. It achieves this through leveraging both user-agnostic and personalized modeling techniques in tandem with an effective ranking strategy to filter predictions.

Keyphrases

machine learning
electronic health record
big data
artificial intelligence
data analysis
cross sectional