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TRIPOD+AI: an updated reporting guideline for clinical prediction models
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TRIPOD+AI: an updated reporting guideline for clinical prediction models (2024)TRIPOD+AI: an updated reporting guideline…TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods (2024)TRIPOD+AI statement: updated …Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review (2022)Completeness of reporting of …PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews (2021)PRISMA 2020 explanation and e…Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension (2020)Reporting guidelines for clin…Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement (2015)Transparent reporting of a mu…CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials (2010)CONSORT 2010 Statement: updat…Comparative accuracy: assessing new tests against existing diagnostic pathways (2006)Comparative accuracy: assessi…Evaluating dental AI research papers: Key considerations for editors and reviewers (2025)Evaluating dental AI research…The Hospital Anxiety and Depression Scale (1983)Towards Complete and Accurate Reporting of Studies of Diagnostic Accuracy: The STARD Initiative (2003)Assessing the value of diagnostic tests: a framework for designing and evaluating trials (2012)GRADE guidelines: 21 part 1. Study design, risk of bias, and indirectness in rating the certainty across a body of evidence for test accuracy (2020)QUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies (2021)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement. (2009)SPIRIT 2013 explanation and elaboration: guidance for protocols of clinical trials (2013)Empirical Evidence of Bias (1995)Empirical evidence of bias. Dimensions of methodological quality associated with estimates of treatment effects in controlled trials (1995)CONSORT 2010 Explanation and Elaboration: updated guidelines for reporting parallel group randomised trials (2010)Advancing health equity with artificial intelligence (2021)Reporting guidelines for clinical trials of artificial intelligence interventions: the SPIRIT-AI and CONSORT-AI guidelines (2021)ESMO Guidance for Reporting Oncology real-World evidence (GROW) (2023)Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)The PRISMA 2020 statement: An updated guideline for reporting systematic reviews (2021)Rayyan—a web and mobile app for systematic reviews (2016)Appraising the Quality of Development and Reporting in Surgical Prediction Models (2022)Reporting and risk of bias of prediction models based on machine learning methods in preterm birth: A systematic review (2022)Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Modeling Studies: Development and Validation (2023)The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for Reporting Observational Studies (2007)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (2009)STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies (2015)STARD 2015: An Updated List of Essential Items for Reporting Diagnostic Accuracy Studies (2015)STARD 2015: an updated list of essential items for reporting diagnostic accuracy studies (2015)Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): Explanation and Elaboration (2015)Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations (2024)PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods (2025)The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence (2025)A manifesto for reproducible science (2017)Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension (2020)Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension (2020)
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References

  • 2021PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews11,660 cited
  • 2010CONSORT 2010 Statement: updated guidelines for reporting parallel group randomised trials9,314 cited
  • 2024TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods4,531 cited
  • 2015Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement4,367 cited
  • 2020Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI Extension695 cited
  • 2006Comparative accuracy: assessing new tests against existing diagnostic pathways459 cited
  • 2022Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review126 cited

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  • 2025Evaluating dental AI research papers: Key considerations for editors and reviewers16 cited

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