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24/10/2024 REFORMS: Consensus-based Recommendations for Machine-learning-based Science 24/01/2024 Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation 18/10/2023 ESMO Guidance for Reporting Oncology real-World evidence (GROW) 10/10/2023 MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care 10/10/2023 Presenting artificial intelligence, deep learning, and machine learning studies to clinicians and healthcare stakeholders: an introductory reference with a guideline and a Clinical AI Research (CAIR) checklist proposal 09/05/2023 CheckList for EvaluAtion of Radiomics research (CLEAR): a step-by-step reporting guideline for authors and reviewers endorsed by ESR and EuSoMII 05/04/2023 Recommendations for Reporting Machine Learning Analyses in Clinical Research 17/03/2022 Standardized Reporting of Machine Learning Applications in Urology: The STREAM-URO Framework 02/10/2020 Proposed Requirements for Cardiovascular Imaging-Related Machine Learning Evaluation (PRIME): A Checklist: Reviewed by the American College of Cardiology Healthcare Innovation Council 07/01/2015 TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

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Latest guest blogger

New resource for research teams to improve the reporting of implementation studies

In this blog post, Dr Louise Hull, an implementation research lead, discusses the development of a new resource to help improve the reporting of implementation studies.