Protocol for a systematic review on the methodological and reporting quality of prediction model studies using machine learning techniques by Andaur Navarro, CL, Damen, JAAG, Takada, T, Nijman, SWJ, Dhiman, P, Ma, J, Collins, GS, Bajpai, R, Riley, RD, Moons, KG, Hooft, L

Systematic review finds "spin" practices and poor reporting standards in studies on machine learning-based prediction models by Andaur Navarro, CL, Damen, JAA, Takada, T, Nijman, SWJ, Dhiman, P, Ma, J, Collins, GS, Bajpai, R, Riley, RD, Moons, KGM, Hooft, L

Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review by Andaur Navarro, CL, Damen, JAA, Takada, T, Nijman, SWJ, Dhiman, P, Ma, J, Collins, GS, Bajpai, R, Riley, RD, Moons, KGM, Hooft, L

Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review by Andaur Navarro, CL, Damen, JAA, Takada, T, Nijman, SWJ, Dhiman, P, Ma, J, Collins, GS, Bajpai, R, Riley, RD, Moons, KGM, Hooft, L

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models by Andaur Navarro, CL, Damen, JAA, van Smeden, M, Takada, T, Nijman, SWJ, Dhiman, P, Ma, J, Collins, GS, Bajpai, R, Riley, RD, Moons, KGM, Hooft, L