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

Viewpoints (31) JMIR Theme Issue: COVID-19 Special Issue (2388) Digital Health, Telehealth and e-Innovation in Clinical Settings (340) Clinical Information and Decision Making (1315) Decision Support for Health Professionals (1129) Chatbots and Conversational Agents (458)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42540, first published .
Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19

Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19

Using Decision Trees as an Expert System for Clinical Decision Support for COVID-19

Authors of this article:

Dillon Chrimes1 Author Orcid Image
Article Authors Cited by (5) Tweetations (8) Metrics

Journals

  1. Giansanti D. The Chatbots Are Invading Us: A Map Point on the Evolution, Applications, Opportunities, and Emerging Problems in the Health Domain. Life 2023;13(5):1130 View
  2. Gholamzadeh M, Abtahi H, Safdari R, Lakshmanna K. The Application of Knowledge-Based Clinical Decision Support Systems to Enhance Adherence to Evidence-Based Medicine in Chronic Disease. Journal of Healthcare Engineering 2023;2023:1 View
  3. BÜLBÜL M. Urinary Bladder Inflammation Prediction with the Gray Wolf Optimization Algorithm and Multi-Layer Perceptron-Based Hybrid Architecture. Bitlis Eren Üniversitesi Fen Bilimleri Dergisi 2023;12(4):1185 View
  4. Kuziemsky C, Chrimes D, Minshall S, Mannerow M, Lau F. AI Quality Standards in Health Care: Rapid Umbrella Review. Journal of Medical Internet Research 2024;26:e54705 View
  5. Olivelli M, Donati M, Vianello A, Petrucci I, Masi S, Bechini A, Fanucci L. Enhancing Precision of Telemonitoring of COVID-19 Patients through Expert System Based on IoT Data Elaboration. Electronics 2024;13(8):1462 View