NEJM AI is an interdisciplinary journal facilitating dialogue among stakeholders invested in using AI to transform medicine. NEJM AI intentionally pairs “pre-clinical” and clinical articles to deliver critical context to both clinicians and non-clinician researchers. The journal bridges the fast-moving developments in AI, informatics, and technology in medicine with the application of these advancements to clinical practice. NEJM AI covers the application of AI methodologies and data science to biomedical informatics, connected health, telemedicine, medical images and imaging, personalized medicine, policy and regulation, and the ethical and medicolegal implications of AI.
Adhering to the rigorous peer-review and quality standards expected from NEJM Group, NEJM AI publishes:
- Original research, including clinical trials of AI or AI assisted diagnosis or therapy, or pre-clinical with breakthrough technology, new medical AI applications, and other rigorous evaluations of medical AI.
- Datasets, Benchmarks, and Protocols, reports describing new datasets, shared benchmarks for the medical machine learning community, and reproducible or novel protocols or study designs that could be adapted for other trials.
- Case Studies, first-person account of the implementation challenges and lessons learned from a specific deployment of medical AI.
- Reviews, peer-reviewed articles of clinically-relevant new machine learning methods, emerging application, and educational topic areas that speak to both machine learning researchers and clinical audiences.
- Perspectives, cover timely, relevant topics in health care and medicine related to AI in a brief, accessible style.
- Policy Corner, longer commentary article that speaks to policy issues around medical AI from perspective of multiple stakeholders (e.g., payers, providers, and patients).
- Editorial, commentary and context for a published original article.
