ArticleFrontiers in digital health2022
Open questions and research gaps for monitoring and updating AI-enabled tools in clinical settings.
Article in Frontiers in digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Artificial intelligence in cardiovascular medicine: a practical guide for clinicians and researchers.European heart journal. Digital health · 2026Review
- Integrating Generative AI Into Patient-Centered Clinical Decision Support: Viewpoint on Research and Practice Considerations.Journal of medical Internet research · 2026Article
- Artificial intelligence in infection surveillance: Data integration, applications and future directions.Biomedical journal · 2026Review
- Comparative performance of LLMs and machine learning in predicting complications after percutaneous kyphoplasty for osteoporotic vertebral compression fractures.NPJ digital medicine · 2026Article
- The unintended negative consequences of artificial intelligence use for psychologists.Frontiers in psychology · 2026Article
- From bedside to bench: towards clinical predictive AI research that achieves real-world impact.BMJ digital health & AI · 2026Review
- Human-centered design of an artificial intelligence monitoring system: the Vanderbilt Algorithmovigilance Monitoring and Operations System.JAMIA open · 2025Article
- Large language models are less effective at clinical prediction tasks than locally trained machine learning models.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Differences in technical and clinical perspectives on AI validation in cancer imaging: mind the gap!European radiology experimental · 2025Article
- Incidence of acute hemorrhagic conjunctivitis in Chongqing: a forecasting study based on mathematical models.Frontiers in public health · 2025Article
- Not the Models You Are Looking For: Traditional ML Outperforms LLMs in Clinical Prediction Tasks.medRxiv : the preprint server for health sciences · 2024Article
- Artificial Intelligence (AI): A Potential Game Changer in Regenerative Orthopedics-A Scoping Review.Indian journal of orthopaedics · 2024Article
- Sustainable deployment of clinical prediction tools-a 360° approach to model maintenance.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Pathophysiological Features in Electronic Medical Records Sustain Model Performance under Temporal Dataset Shift.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2024Article
- Challenges and Future Perspectives for Artificial Intelligence in Hepatology: Breaking Barriers for Better Care.Journal of clinical and experimental hepatologyReview
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3 authors.
Funding
Abstract
As the implementation of artificial intelligence (AI)-enabled tools is realized across diverse clinical environments, there is a growing understanding of the need for ongoing monitoring and updating of prediction models. Dataset shift-temporal changes in clinical practice, patient populations, and information systems-is now well-documented as a source of deteriorating model accuracy and a challenge to the sustainability of AI-enabled tools in clinical care. While best practices are well-established for training and validating new models, there has been limited work developing best practices for prospective validation and model maintenance. In this paper, we highlight the need for updating clinical prediction models and discuss open questions regarding this critical aspect of the AI modeling lifecycle in three focus areas: model maintenance policies, performance monitoring perspectives, and model updating strategies. With the increasing adoption of AI-enabled tools, the need for such best practices must be addressed and incorporated into new and existing implementations. This commentary aims to encourage conversation and motivate additional research across clinical and data science stakeholders.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.