Reporting of artificial intelligence prediction models von Collins, Gary S, Moons, Karel G M

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Using Causal Diagrams to Improve the Design and Interpretation of Medical Research von Etminan, Mahyar, Collins, Gary S., Mansournia, Mohammad Ali

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Sample size considerations for the external validation of a multivariable prognostic model: a resampling study von Collins, Gary S., Ogundimu, Emmanuel O., Altman, Douglas G.

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Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies von Nagendran, Myura, Chen, Yang, Lovejoy, Christopher A, Gordon, Anthony C, Komorowski, Matthieu, Harvey, Hugh, Topol, Eric J, Ioannidis, John P A, Collins, Gary S, Maruthappu, Mahiben

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Minimum sample size for developing a multivariable prediction model: PART II ‐ binary and time‐to‐event outcomes von Riley, Richard D, Snell, Kym IE, Ensor, Joie, Burke, Danielle L, Harrell Jr, Frank E, Moons, Karel GM, Collins, Gary S

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Guidelines for Accurate and Transparent Health Estimates Reporting: the GATHER statement von Stevens, Gretchen A, Dr, Alkema, Leontine, PhD, Black, Robert E, Prof, Boerma, J Ties, PhD, Collins, Gary S, PhD, Ezzati, Majid, Prof, Grove, John T, PhD, Hogan, Daniel R, PhD, Hogan, Margaret C, PhD, Horton, Richard, FMedSci, Lawn, Joy E, Prof, Marušić, Ana, Prof, Mathers, Colin D, PhD, Murray, Christopher J L, Prof, Rudan, Igor, Prof, Salomon, Joshua A, Prof, Simpson, Paul J, PhD, Vos, Theo, Prof, Welch, Vivian, PhD

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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement von Collins, Gary S, Reitsma, Johannes B, Altman, Douglas G, Moons, Karel G M

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Reflection on modern methods: demystifying robust standard errors for epidemiologists von Mansournia, Mohammad Ali, Nazemipour, Maryam, Naimi, Ashley I, Collins, Gary S, Campbell, Michael J

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Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance von Nguyen, Tri-Long, Collins, Gary S, Spence, Jessica, Daurès, Jean-Pierre, Devereaux, P J, Landais, Paul, Le Manach, Yannick

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Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting von Collins, Gary S, Mallett, Susan, Omar, Omar, Yu, Ly-Mee

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Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist von Moons, Karel G M, de Groot, Joris A H, Bouwmeester, Walter, Vergouwe, Yvonne, Mallett, Susan, Altman, Douglas G, Reitsma, Johannes B, Collins, Gary S

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Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intellig... von Collins, Gary S, Dhiman, Paula, Andaur Navarro, Constanza L, Ma, Jie, Hooft, Lotty, Reitsma, Johannes B, Logullo, Patricia, Beam, Andrew L, Peng, Lily, Van Calster, Ben, van Smeden, Maarten, Riley, Richard D, Moons, Karel GM

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External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: opportunities and challenges von Riley, Richard D, Ensor, Joie, Snell, Kym I E, Debray, Thomas P A, Altman, Doug G, Moons, Karel G M, Collins, Gary S

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Burden of anemia and its underlying causes in 204 countries and territories, 1990-2019: results from the Global Burden of Disease Study 2019 von Safiri, Saeid, Kolahi, Ali-Asghar, Noori, Maryam, Nejadghaderi, Seyed Aria, Karamzad, Nahid, Bragazzi, Nicola Luigi, Sullman, Mark J. M., Abdollahi, Morteza, Collins, Gary S., Kaufman, Jay S., Grieger, Jessica A.

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Sample size for binary logistic prediction models: Beyond events per variable criteria von van Smeden, Maarten, Moons, Karel GM, de Groot, Joris AH, Collins, Gary S, Altman, Douglas G, Eijkemans, Marinus JC, Reitsma, Johannes B

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Minimum sample size for developing a multivariable prediction model: Part I – Continuous outcomes von Riley, Richard D., Snell, Kym I.E., Ensor, Joie, Burke, Danielle L., Harrell, Frank E., Moons, Karel G.M., Collins, Gary S.

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Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness von Vollmer, Sebastian, Mateen, Bilal A, Bohner, Gergo, Király, Franz J, Ghani, Rayid, Jonsson, Pall, Cumbers, Sarah, Jonas, Adrian, McAllister, Katherine S L, Myles, Puja, Granger, David, Birse, Mark, Branson, Richard, Moons, Karel G M, Collins, Gary S, Ioannidis, John P A, Holmes, Chris, Hemingway, Harry

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Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD): The TRIPOD Statement von Collins, Gary S, Reitsma, Johannes B, Altman, Douglas G, Moons, Karel G.M

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No rationale for 1 variable per 10 events criterion for binary logistic regression analysis von van Smeden, Maarten, de Groot, Joris A H, Moons, Karel G M, Collins, Gary S, Altman, Douglas G, Eijkemans, Marinus J C, Reitsma, Johannes B

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External validation of multivariable prediction models: a systematic review of methodological conduct and reporting von Collins, Gary S, de Groot, Joris A, Dutton, Susan, Omar, Omar, Shanyinde, Milensu, Tajar, Abdelouahid, Voysey, Merryn, Wharton, Rose, Yu, Ly-Mee, Moons, Karel G, Altman, Douglas G

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