On September 30, 2025, JAMA issued a call for papers on AI, with a long wish list.
https://jamanetwork.com/journals/jama/fullarticle/2839356
It's open-access, so I've clipped the request below, which shows the span of issues for these editors. Since it's fairly long, I've also included a short AI summary at top.
### AI Summary
AMA highlights that AI in medicine is shifting from proof-of-concept to rigorous clinical evaluation.
With over 1000 FDA-cleared AI/ML devices already in use, the field now needs evidence of impact, safety, equity, and efficiency. The JAMA Network seeks manuscripts on clinical applications of AI, including head-to-head outcome comparisons, workflow and equity effects, ambient documentation tools, public trust, and generalizability across populations.
Submissions should follow TRIPOD+AI, DECIDE-AI, and CLEAR reporting standards, and external validation is emphasized. Readers and authors are invited to explore ongoing insights via JAMA+ AI (jamaai.org).
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JAMA Editors:
Few technologies have generated enthusiasm in medicine as rapidly and intensely as artificial intelligence (AI), often outstripping the research community’s capacity to study its impact. The explosion in interest in both research and implementation of AI in medicine is driven by a leap in the ability of these tools to analyze and synthesize data derived from written text, wearable technology, and images. For example, deep learning–based image analysis has enabled the prediction of pathologic gene sequence variations directly from digital histopathology slides in oncology1 and demonstrated that insights exceeding expert human capability could be derived in specific use cases. To date, the US Food and Drug Administration (FDA) has authorized for marketing more than 1000 AI- and machine learning–enabled medical devices2 designed for a wide range of applications, such as predictive analytics, clinical decision support, and deep phenotyping. The ability of large language models to recognize patterns in unstructured text and speech has already been used to dramatic effect, such as ambient scribing in clinical settings.
The journals of the JAMA Network believe AI applications will play an increasingly important role in the science and practice of medicine. We, as a network, are committed to ensuring that clinicians and policymakers have the evidence they need to make informed decisions about how and when they apply these new technologies. The application of AI to medicine is at a point of inflection, transitioning from proof-of-concept studies that demonstrate the potential of these technologies to later-stage investigations that apply more rigorous methodologies and aim to establish impact, safety, equity, efficacy, and efficiency.
Across the JAMA Network, we are seeking submission of manuscripts describing original research that examines the application of AI in clinical settings across all of these stages. We seek to support innovation across medicine and public health while upholding the highest standards for scientific rigor. Although adequately powered, prospective randomized clinical trials remain the gold standard in clinical medicine, we also welcome alternative study designs for the evaluation of AI tools, such as real-world evidence studies and proof-of-concept studies that involve validation by independent, external datasets. External, independent validation is particularly crucial for AI models used for risk stratification and treatment recommendation. Although the JAMA Network journals are generally interested in clinically impactful studies, the following list of topics will also be of particular interest:
Head-to-head comparisons of clinical outcomes between various workflows or strategies using AI, compared with standard of care or other gold standards.
Translational, computational to bedside AI studies that evaluate how AI tools are used in practice (including “off-label use”) and how the deployment of FDA-cleared clinical AI tools affects population-level metrics beyond efficacy, including workflow, referral patterns, access, equity, bias, and quality metrics.
AI products or tools focused on increasing efficiency and reducing health care professional workloads, such as ambient scribes, clinical documentation summarization, and generative AI products for revenue cycle management.
Public or patient perception and trust in specific AI tools or use of these tools in clinical workflows.
Evaluation of existing AI tools—rather than repeatedly reinventing them from scratch—across diverse populations to ensure their generalizability beyond the specific cohorts originally studied.
We expect AI manuscripts submitted to the JAMA Network will adhere to the appropriate reporting standards and guidelines outlined by frameworks3 such as TRIPOD+AI, DECIDE-AI, and CLEAR. For additional AI-related studies and insights, we encourage readers and authors to explore JAMA+ AI at jamaai.org. This channel features in-depth AI research, conducts exclusive interviews with leading experts and authors, and highlights the diverse studies published across the entire JAMA Network, including, we hope, those this call for submissions will elicit.
