Regarding a nomogram to predict osteoradionecrosis in oral cancer after marginal mandibulectomy and radiotherapy by Collins, GS, Van Calster, B

Artificial intelligence algorithms for medical prediction should be nonproprietary and readily available by Van Calster, B, Steyerberg, E, Collins, G

A note on estimating the Cox-Snell R2 from a reported C statistic (AUROC) to inform sample size calculations for developing a prediction model with a binary outcome by Riley, RD, Van Calster, B, Collins, GS

Consequences of relying on statistical significance: some illustrations by Van Calster, B, Steyerberg, E, Collins, G, Smits, T

Statistics versus machine learning: definitions are interesting (but understanding, methodology, and reporting are more important) by Van Calster, B, Verbakel, JY, Christodoulou, E, Steyerberg, EW, Collins, GS

Predictive analytics in health care: how can we know it works? by Van Calster, B, Wynants, L, Timmerman, D, Steyerberg, E, Collins, G

ROC curves for clinical prediction models part 3. The ROC plot: a picture that needs a 1000 words by Van Calster, B, Wynants, L, Collins, GS, Verbakel, JY, Steyerberg, EW

Understanding overfitting in random forest for probability estimation: a visualization and simulation study by Barreñada, L, Dhiman, P, Timmerman, D, Boulesteix, A, Van Calster, B

Methodology over metrics: current scientific standards are a disservice to patients and society by Van Calster, B, Wynants, L, Riley, RD, van Smeden, M, Collins, GS

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models by Evangelia, C, Jie, M, Collins, G, Steyerberg, E, Verbakel, J, Van Calster, B

Flawed external validation study of the ADNEX model to diagnose ovarian cancer. by Van Calster, B, Steyerberg, E, Bourne, T, Timmerman, D, Collins, G, TG6 of the STRATOS initiative

Transparent reporting of multivariable prediction models developed or validated using clustered data: TRIPOD-Cluster checklist by Debray, TPA, Collins, GS, Riley, RD, Snell, KIE, Van Calster, B, Reitsma, JB, Moons, KGM

Transparent reporting of multivariable prediction models developed or validated using clustered data (TRIPOD-Cluster): explanation and elaboration by Debray, TPA, Collins, GS, Riley, RD, Snell, KIE, Van Calster, B, Reitsma, JB, Moons, KGM

ROC curves for clinical prediction models part 1. ROC plots showed no added value above the AUC when evaluating the performance of clinical prediction models by Verbakel, JY, Steyerberg, EW, Uno, H, De Cock, B, Wynants, L, Collins, GS, Van Calster, B

Minimum sample size for developing a multivariable prediction model using multinomial logistic regression by Pate, A, Riley, RD, Collins, GS, van Smeden, M, Van Calster, B, Ensor, J, Martin, GP

Utility of pre-operative haemoglobin concentration to guide peri-operative blood tests for hip and knee arthroplasty: a decision curve analysis by Dhiman, P, Gibbs, VN, Collins, GS, Van Calster, B, Bakhishli, G, Grammatopoulos, G, Price, AJ, Taylor, A, Murphy, MF, Kendrick, BJL, Palmer, AJR

Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved by Dhiman, P, Ma, J, Navarro, CA, Speich, B, Bullock, G, Damen, JA, Kirtley, S, Hooft, L, Riley, RD, Van Calster, B, Moons, KGM, Collins, GS

Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review by Dhiman, P, Ma, J, Andaur Navarro, CL, Speich, B, Bullock, G, Damen, JAA, Hooft, L, Kirtley, S, Riley, RD, Van Calster, B, Moons, KGM, Collins, GS

Risk of bias of prognostic models developed using machine learning: a systematic review in oncology by Dhiman, P, Ma, J, Andaur Navarro, CL, Speich, B, Bullock, G, Damen, JAA, Hooft, L, Kirtley, S, Riley, RD, Van Calster, B, Moons, KGM, Collins, GS

Methodological conduct of prognostic prediction models developed using machine learning in oncology: a systematic review by Dhiman, P, Ma, J, Andaur Navarro, CL, Speich, B, Bullock, G, Damen, JAA, Hooft, L, Kirtley, S, Riley, RD, Van Calster, B, Moons, KGM, Collins, GS