Diagnostic errors remain a major source of preventable patient harm, particularly in low- and middle-income countries. Large language models (LLMs) have the potential to bridge these gaps in diagnostic capacity, but can generate inaccurate information, necessitating artificial intelligence (AI)-literacy training. However, whether AI-trained physicians can leverage LLMs to improve diagnostic reasoning compared with conventional resources…
Nature Health Template
Write in a clean editor, then format for Nature Health in one click — DocuGuru applies the official Springer Nature template with superscript references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
About the Nature Health format
Nature Health is a peer-reviewed journal published by Springer Nature, covering Artificial Intelligence in Healthcare and Education, Global Health and Surgery, Climate Change and Health Impacts. Over its lifetime it has published 154 papers, which have received 157 citations.
| Publisher | Springer Nature |
|---|---|
| Reference style | Superscript numbered (Nature) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. Nature Health 12, 45–58 (2023).
Formats any DOI in Nature Health style. No sign-up. |
| Publishes research in | Artificial Intelligence in Healthcare and Education Global Health and Surgery Climate Change and Health Impacts Machine Learning in Healthcare Global Maternal and Child Health |
| Papers published last year | ≈3 |
| ISSN | 3005-0693 |
| Citation impact (2-yr) | 1.02 |
| h-index | 5 |
| i10-index | 3 |
| Top institutions publishing here | Harvard University |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Most-cited papers in Nature Health
Abstract Global physical inactivity has remained high and unchanged for the past two decades. We assessed global political priority for physical activity. An analysis of national policy documents from 200 countries revealed notable progress in policy adoption since 2004, but we found limited evidence of implementation. A qualitative case study design, including insights from 46…
Large language models (LLMs) are emerging as powerful tools in healthcare, with a growing role in global health, particularly in low- and middle-income countries (LMICs). This Perspective examines the current progress, challenges and prospects of LLMs in addressing health system disparities and supporting the achievement of the Sustainable Development Goals (SDGs). While high-income countries dominate…
Here we conducted a retrospective evaluation of an electronic medical record-embedded large language model clinical decision support system deployed across 16 primary care clinics in Kenya, between July and September 2024. A panel of trained physicians reviewed 1,469 records. Hallucinations were uncommon, occurring in 50 encounters (3.4%, 95% confidence interval (CI) 2.5-4.5), and most often…