Nursing workforce forecasting | Division of Health AI

Division project · Active

Machine learning models using DeepAR probabilistic forecasting predict nursing workforce demand across Northwell's hospital units up to 12 months ahead, supporting preemptive hiring and staffing decisions across diverse specialties.

Twelve-month forecasts of nursing demand for four representative hospital units, with 50% and 90% prediction intervals around the mean prediction.IEEE EMBC, 2025 · © 2025 IEEE, authors' reuse (opens in new tab)

Status: Active
Program: Division project
Publications: 1, latest 2025
Team: 4 members

On this project

Nabil Ettehadi, PhD

AI/ML Advisor

Diego Gonzalez Garcia-Torres

IT&S Project Coordinator

Todd Levy, MS

Senior Biomedical Engineer

Theodoros Zanos, PhD

Professor & AVP

From the papers

Published figures

Figures reproduced from the papers behind this project. Each panel keeps its original source and license.

Nurse headcount across the 38 unit and specialty combinations used to train the model, ranging from about 100 to 1,000 employees each. IEEE EMBC, 2025 (opens in new tab) · © 2025 IEEE, authors' reuse

Publication

View in the index

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)Jul 2025

An Artificial Intelligence-Based Probabilistic Forecasting Model for Predicting Nursing Workforce Demand in Hospital Units

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