Juan Guillermo Diaz Ochoa

The paper introduces a method to assess causal relationships in dynamic biological systems using geometric information theory and persistent homology, demonstrating its application to ICU and wearable health data.

The paper introduces a method using homology groups to detect persistent anomalies in time series data from patients, aiming to improve model validity through pattern clustering and causal relationship identification.