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D-Index & Metrics

Medicine

D-Index
100
Citations
74198
World Ranking
8098
National Ranking
794

Overview

Gary S. Collins is affiliated with the University of Oxford in the United Kingdom. Their primary field of study is Medicine, with a focus on several subfields including Statistics, Probability and Uncertainty, Surgery, Economics and Econometrics, Health Informatics, and Artificial Intelligence.

The scientist's research covers key topics such as Meta-analysis and systematic reviews, Artificial Intelligence in Healthcare and Education, Health Systems, Economic Evaluations, Quality of Life, Machine Learning in Healthcare, Sports injuries and prevention, Sepsis Diagnosis and Treatment, and Radiomics and Machine Learning in Medical Imaging.

Recent significant publications by Gary S. Collins include:

  • TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods, 2024, BMJ
  • Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal, 2020, BMJ
  • Calculating the sample size required for developing a clinical prediction model, 2020, BMJ
  • Global, regional and national burden of osteoarthritis 1990-2017: a systematic analysis of the Global Burden of Disease Study 2017, 2020, Annals of the Rheumatic Diseases
  • Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the Global Burden of Disease Study 2021, 2023, The Lancet Rheumatology

The venues where Gary S. Collins has published most frequently include:

  • BMJ
  • Journal of Clinical Epidemiology
  • BMJ Open
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature Medicine

Frequent co-authors collaborating with Collins are:

  • Richard D Riley
  • Paula Dhiman
  • Garrett S. Bullock
  • Ben Van Calster
  • Karel G.M. Moons

Best Publications

  • Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): the TRIPOD Statement.

    G S Collins;J B Reitsma;D G Altman;K G M Moons

  • Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration.

    Karel G.M. Moons;Douglas G. Altman;Johannes B. Reitsma;John P.A. Ioannidis

  • Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal

    Laure Wynants;Laure Wynants;Ben Van Calster;Ben Van Calster;Gary S Collins;Gary S Collins;Richard D Riley

  • Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER Statement

    Gretchen A. Stevens;Leontine Alkema;Robert E. Black;J. Ties Boerma

  • Global, regional and national burden of osteoarthritis 1990-2017: A systematic analysis of the Global Burden of Disease Study 2017

    Saeid Safiri;Ali Asghar Kolahi;Damian Hoy;Emma Smith

  • PROBAST: A tool to assess the risk of bias and applicability of prediction model studies

    Robert F. Wolff;Karel G.M. Moons;Richard D. Riley;Penny F. Whiting

  • Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist.

    Karel G. M. Moons;Joris A. H. de Groot;Walter Bouwmeester;Yvonne Vergouwe

  • Calculating the sample size required for developing a clinical prediction model.

    Richard D Riley;Joie Ensor;Kym I E Snell;Frank E Harrell

  • A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

    Evangelia Christodoulou;Jie Ma;Gary S. Collins;Ewout W. Steyerberg

  • PROBAST : A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration

    Karel G.M. Moons;Robert F. Wolff;Richard D. Riley;Penny F. Whiting

  • Prediction models for cardiovascular disease risk in the general population: systematic review

    Johanna A A G Damen;Lotty Hooft;Ewoud Schuit;Ewoud Schuit;Thomas P A Debray

  • Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies

    Myura Nagendran;Yang Chen;Christopher A Lovejoy;Anthony C Gordon;Anthony C Gordon

  • Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes

    Richard D. Riley;Kym I.E. Snell;Joie Ensor;Danielle L. Burke

  • External validation of multivariable prediction models: a systematic review of methodological conduct and reporting.

    Gary S. Collins;Joris A. De Groot;Susan Dutton;Omar Omar

  • Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. The TRIPOD Group.

    Gary S. Collins;Johannes B. Reitsma;Douglas G. Altman;Karel G.M. Moons

  • Sample size considerations for the external validation of a multivariable prognostic model: a resampling study.

    Gary S. Collins;Emmanuel O. Ogundimu;Douglas G. Altman

  • COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

    Lee Lyw.;Cazier J-B.;T Starkey;Briggs Sew.

  • Reporting of artificial intelligence prediction models.

    Gary S Collins;Karel G M Moons

  • Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection

    L Wynants;B Van Calster;Bonten Mmj.;G Collins

  • Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies in medical imaging.

    M Nagendran;Y Chen;C A Lovejoy;A C Gordon

Frequent Co-Authors

Douglas G. Altman
Douglas G. Altman University of Oxford
Karel G.M. Moons
Karel G.M. Moons Utrecht University
Nigel K. Arden
Nigel K. Arden University of Oxford
Johannes B. Reitsma
Johannes B. Reitsma Utrecht University
Sarah E Lamb
Sarah E Lamb University of Exeter
Andrew Judge
Andrew Judge University of Bristol
Sally Hopewell
Sally Hopewell University of Oxford
Andrew Carr
Andrew Carr University of Oxford
Mohammad Ali Mansournia
Mohammad Ali Mansournia Tehran University of Medical Sciences
Ewout W. Steyerberg
Ewout W. Steyerberg Leiden University Medical Center

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