Accessibility settings

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

AI Applications in Biomedical Engineering (44) Clinical Information and Decision Making (3868) Natural Language Processing (1326) Symptom Checkers (68) Generative Language Models Including ChatGPT (1615) AI Language Models in Health Care (816)

Published on in Vol 11 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/88053, first published .
Woman drinking tea while looking at a computer screen displaying the word "CARE" and makeup icons.

Increasing Large Language Model Accuracy for Care-Seeking Advice Using Prompts Reflecting Human Reasoning Strategies in the Real World: Validation Study

Increasing Large Language Model Accuracy for Care-Seeking Advice Using Prompts Reflecting Human Reasoning Strategies in the Real World: Validation Study

Authors of this article:

Marvin Kopka1 Author Orcid Image ;   Markus A Feufel1 Author Orcid Image
Article Authors Cited by (2) Tweetations (1) Metrics

Journals

  1. Diyasena H, Ahmad A, Weerasinghe T, Crawshaw O, O'Brien A. Comparative Error Analysis of GPT-5.2 Reasoning Modes on Performance in Postgraduate Internal Medicine Single-Best-Answer Questions. Cureus 2026 View
  2. Luo W, Lu G. Nurse-led digital triage and health literacy navigation: redefining the front door of public health in the artificial intelligence era. Frontiers in Public Health 2026;14 View