Predictive Analytics & Machine Learning | NYU Langone Health

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Center for Healthcare Innovation & Delivery Science Predictive Analytics & Machine Learning

Predictive Analytics & Machine Learning

The Predictive Analytics Unit in the Center for Healthcare Innovation and Delivery Science uses data and modeling to predict health outcomes across NYU Langone. Our goal is to help clinicians and other staff in our health system make important clinical decisions in real time, increase operational efficiency, and develop as a learning healthcare system.

Led by Yindalon Aphinaynaphongs, MD, PhD, we develop, test, implement, and evaluate predictive models, many using artificial intelligence (AI) methods, to improve care. Clinical models currently in use include prediction of patients at risk of deterioration, patients who have sepsis, and patients at high risk of near-term mortality. Operational models currently in use include prediction of no-show visits and identification of patients with active diseases that have not been recorded in the electronic health record.

We also use our electronic health record data combined with AI methods to forecast and prevent onset of disease. Conditions of interest include dialysis and kidney failure, congestive heart failure, stroke, breast cancer, prostate cancer, lung cancer, type 2 diabetes, hospital-acquired infections, adverse drug interactions, emergency department visits, and rehospitalization, among others.

Our group routinely offers the following services:

  • provide internal capacity for predictive modeling at NYU Langone to facilitate real-time clinical decision-making, increase operational efficiency, and build foundation for a learning healthcare system
  • lead specific projects from inception through development, deployment, and evaluation
  • provide education and professional development to support building a data-driven organization
  • build community for clinical data science across NYU Langone
  • facilitate external collaborations
  • vet commercial AI-based technologies for implementation at NYU Langone

Learn more about our team and specific analyses.

Contact Us

If you have questions or an idea for a proposal for a model to be built at NYU Langone, please email us at

Selected Predictive Analytics and Machine Learning Publications

Hammond R … Elbel B. Predicting childhood obesity using electronic health records and publicly available data. PLoS One. 2019. DOI.

Coudray N … Tsirigos A. Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning. Nat Med. 2018. DOI.

Liu J, Zhang Z, and Razavian N. Deep EHR: Chronic disease prediction using medical notes. Proceedings of the 3rd Machine Learning for Healthcare Conference. 2018. 85:440–464.

Aphinyanaphongs Y. Big data analyses in health and opportunities for research in radiology. Semin Musculoskelet Radiol. 2017. DOI.

Blecker S … Katz SD. Early identification of patients with acute decompensated heart failure. J Card Fail. 2017. DOI.

Blecker S … Sontag D. Comparison of approaches for heart failure case identification from electronic health record data. JAMA Cardiology. 2016. DOI.