This paper is in the following e-collection/theme issue:

Tutorial (64) Artificial Intelligence (1371) Clinical Information and Decision Making (1407) Machine Learning (1465)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50890, first published .
Machine Learning and Health Science Research: Tutorial

Machine Learning and Health Science Research: Tutorial

Machine Learning and Health Science Research: Tutorial

Authors of this article:

Hunyong Cho1 Author Orcid Image ;   Jane She1 Author Orcid Image ;   Daniel De Marchi1 Author Orcid Image ;   Helal El-Zaatari1 Author Orcid Image ;   Edward L Barnes2, 3 Author Orcid Image ;   Anna R Kahkoska4, 5, 6 Author Orcid Image ;   Michael R Kosorok1 Author Orcid Image ;   Arti V Virkud7 Author Orcid Image
Article Authors Cited by (4) Tweetations (16) Metrics

Journals

  1. Hasni N. Critical Review on the Contribution of Machine Learning to Health Science. Web3 Journal: ML in Health Science 2024;1(2) View
  2. Xia Q, Deng C, Yang S, Gu N, Shen Y, Shi B, Zhao R. Machine Learning Constructed Based on Patient Plaque and Clinical Features for Predicting Stent Malapposition: A Retrospective Study. Clinical Cardiology 2024;47(8) View
  3. Romero Martínez M, Pozuelo Campillo J, Carmona Ibáñez P. Ethical transparency in business failure prediction: uncovering the black box of xgboost algorithm. Spanish Journal of Finance and Accounting / Revista Española de Financiación y Contabilidad 2024:1 View
  4. Bikaki A, Luningham J, Thompson E, Krenek B, Vishwanatha J, Kakadiaris I. Identifying influential factors using machine learning techniques on the intention to receive a COVID-19 booster dose and vaccine fatigue among partially vaccinated individuals. Discover Public Health 2024;21(1) View