Published on in Vol 8, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16129, first published .
Precision Health–Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation

Precision Health–Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation

Precision Health–Enabled Machine Learning to Identify Need for Wraparound Social Services Using Patient- and Population-Level Data Sets: Algorithm Development and Validation

Journals

  1. Jalilian L, Cannesson M. Precision medicine in anesthesiology. International Anesthesiology Clinics 2020;58(4):17 View
  2. Schleyer T, Williams L, Gottlieb J, Weaver C, Saysana M, Azar J, Sadowski J, Frederick C, Hui S, Kara A, Ruppert L, Zappone S, Bushey M, Grout R, Embi P. The Indiana Learning Health System Initiative: Early experience developing a collaborative, regional learning health system. Learning Health Systems 2021;5(3) View
  3. Berg K, Doktorchik C, Quan H, Saini V. Automating data collection methods in electronic health record systems: a Social Determinant of Health (SDOH) viewpoint. Health Systems 2023;12(4):472 View
  4. Kasturi S, Park J, Wild D, Khan B, Haggstrom D, Grannis S. Predicting COVID-19–Related Health Care Resource Utilization Across a Statewide Patient Population: Model Development Study. Journal of Medical Internet Research 2021;23(11):e31337 View
  5. Balters S, Gowda N, Ordonez F, Paredes P. Individualized stress detection using an unmodified car steering wheel. Scientific Reports 2021;11(1) View

Books/Policy Documents

  1. Shoenbill K, Kasturi S, Mendonca E. Chronic Illness Care. View
  2. Dixon B, Barros Sierra Cordera D, Hernández Ávila M, Wang X, Zhang L, Romero W, Zepeda Tello R. Modernizing Global Health Security to Prevent, Detect, and Respond. View