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BMC Medical Research Methodology|January 14, 2022
Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic reviewConstanza L Andaur Navarro, Johanna A A Damen, Toshihiko Takada, et al.
BMJ Open|November 12, 2020
Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniquesConstanza L Andaur Navarro, Johanna A A G Damen, Toshihiko Takada, et al.
BMJ (Clinical Research Ed.)|October 21, 2021
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic reviewConstanza L Andaur Navarro, Johanna A A Damen, Toshihiko Takada, et al.
Journal of Clinical Epidemiology|April 6, 2023
Systematic review finds "spin" practices and poor reporting standards in studies on machine learning-based prediction modelsConstanza L Andaur Navarro, Johanna A A Damen, Toshihiko Takada, et al.
Physical Review Letters|July 13, 2004
Atom movement in In3La studied via nuclear quadrupole relaxationMatthew O Zacate, Aurélie Favrot, Gary S Collins
Chest|July 14, 2020
Using Causal Diagrams to Improve the Design and Interpretation of Medical ResearchMahyar Etminan, Gary S Collins, Mohammad Ali Mansournia
Diagnostic and Prognostic Research|July 6, 2022
Risk of bias of prognostic models developed using machine learning: a systematic review in oncologyPaula Dhiman, Jie Ma, Constanza L Andaur Navarro, et al.
Journal of Clinical Epidemiology|March 19, 2023
Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic reviewPaula Dhiman, Jie Ma, Constanza L Andaur Navarro, et al.
BMC Medical Research Methodology|July 2, 2025
Extended sample size calculations for evaluation of prediction models using a threshold for classificationRebecca Whittle, Joie Ensor, Lucinda Archer, et al.
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