Dynamic Healthcare Embeddings for Improving Patient Care

1 code implementation • 21 Mar 2023 • Hankyu Jang, Sulyun Lee, D. M. Hasibul Hasan, Philip M. Polgreen, Sriram V. Pemmaraju, Bijaya Adhikari

Here, we propose DECENT, an auto-encoding heterogeneous co-evolving dynamic neural network, for learning heterogeneous dynamic embeddings of patients, doctors, rooms, and medications from diverse data streams.

severity prediction

21 Million Opportunities: A 19 Facility Investigation of Factors Affecting Hand Hygiene Compliance via Linear Predictive Models

no code implementations • 26 Jan 2018 • Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre

This large-scale study, consisting of 21. 3 million hand hygiene opportunities from 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand hygiene compliance.

A Large-Scale Exploration of Factors Affecting Hand Hygiene Compliance Using Linear Predictive Models

no code implementations • 6 May 2017 • Michael T. Lash, Jason Slater, Philip M. Polgreen, Alberto M. Segre

This large-scale study, consisting of 24. 5 million hand hygiene opportunities spanning 19 distinct facilities in 10 different states, uses linear predictive models to expose factors that may affect hand hygiene compliance.