Neighborhood-level risk factors for severe hyperglycemia among ED patients without a prior diabetes diagnosis
Christian Koziatek, Isaac Bohart, [...], Daniel B. Neill, David LeeRead more
PROVIDENT: development and validation of a machine learning model to predict neighborhood-level overdose risk in Rhode Island
Bennett Allen, [...], Magdalena Cerda, Daniel B. NeillRead more
Fairness and bias of machine learning in healthcare and medicine
Isaac Bohart, Daniel B. Neill, and David LeeRead more
Identifying predictors of opioid overdose death at a neighborhood level with machine learning
R. C. Schell, B. Allen, W. C. Goedel, B. D. Hallowell, R. Scagos, Y. Li, M. S. Krieger, D. B. Neill, B. D. L. Marshall, M. Cerda, and J. AhernRead more
Detecting anomalous networks of opioid prescribers and dispensers in prescription drug data
Presyndromic surveillance for improved detection of emerging public health threats
Mallory Nobles, Ramona Lall, Robert W. Mathes, and Daniel B. NeillRead more
Preventing overdose using information and data from the environment (PROVIDENT): Protocol for a randomised, population-based, community intervention trial
B. D. L. Marshall, N. Alexander-Scott, J. L. Yedinak, B. Hallowell, W. C. Goedel, B. Allen, R. C. Schell, M. S. Krieger, C. Pratty, J. Ahern, D. B. Neill, and M. CerdaRead more
Translating predictive analytics for public health practice: a case study of overdose prevention in Rhode Island
B. Allen, D. B. Neill, R. C. Schell, J. Ahern, B. Hallowell, M. Krieger, V. A. Jent, W. C. Goedel, A. R. Cartus, J. L. Yedinak, C. Pratty, B. D. L. Marshall, and M. CerdaRead more
Chronic Medication Burden for Patients After Congenital Heart Surgery: A 14-Year Statewide Analysis of Publicly Insured Patients