COLA-GLM: Collaborative One-Shot and Lossless Algorithms of Generalized Linear Models for Decentralized Observational Healthcare Data

COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data

Clinical insights from real-world data often require aggregating information from institutions to ensure sufficient sample sizes and generalizability. However, patient privacy concerns only limit the sharing of patient-level data, and traditional federated learning algorithms, relying on extensive back-and-forth communications, can be inefficient to implement. We introduce the Collaborative One-shot Lossless Algorithm for Generalized Linear Mode…

Privacy's Next Frontier: Understanding Federated Learning for Data Security

Keen to discover how federated learning is revolutionizing data security? Uncover the secrets behind this innovative approach that keeps your information safe.