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Publications

Sample size requirements are not being considered in studies developing prediction models for binary outcomes: a systematic review.

Dhiman P. et al, (2023), Bmc med res methodol, 23

Poor handling of continuous predictors in clinical prediction models using logistic regression: a systematic review.

Ma J. et al, (2023), J clin epidemiol

Systematic review highlights high risk of bias of clinical prediction models for blood transfusion in patients undergoing elective surgery.

Dhiman P. et al, (2023), J clin epidemiol, 159, 10 - 30

Systematic review finds "Spin" practices and poor reporting standards in studies on machine learning-based prediction models.

Andaur Navarro CL. et al, (2023), J clin epidemiol

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models.

Andaur Navarro CL. et al, (2022), J clin epidemiol

Multivariable prediction models for atrial fibrillation after cardiac surgery: a systematic review protocol

Bedford J. et al, (2022)

Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review.

Andaur Navarro CL. et al, (2022), Bmc med res methodol, 22

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review.

Andaur Navarro CL. et al, (2021), Bmj, 375

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 intelligence.

Collins GS. et al, (2021), Bmj open, 11

Completeness of reporting of clinical prediction models developed using supervised machine learning: A systematic review

Andaur Navarro CL. et al, (2021)

There are no shortcuts in the development and validation of a COVID-19 prediction model.

Collins GS. et al, (2021), Transbound emerg dis, 68, 210 - 211

Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques.

Andaur Navarro CL. et al, (2020), Bmj open, 10

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

Wynants L. et al, (2020), Bmj, m1328 - m1328

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

Christodoulou E. et al, (2019), J clin epidemiol, 110, 12 - 22

Risk prediction models in perioperative medicine: methodological considerations

Collins GS. et al, (2016), Current anesthesiology reports

Assessing the impact of handling missing data when validating a prognostic model.

Ma J. et al, (2016)

Clinical prediction models: a critical review of online risk calculators

Ma J. et al, (2016)

Include forthcoming?