Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
Objective To assess the methodological quality of studies on prediction models developed
using machine learning techniques across all medical specialties. Design Systematic …
using machine learning techniques across all medical specialties. Design Systematic …
[HTML][HTML] Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models
Abstract Background and Objectives We sought to summarize the study design, modelling
strategies, and performance measures reported in studies on clinical prediction models …
strategies, and performance measures reported in studies on clinical prediction models …
TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …
[HTML][HTML] Completeness of reporting of clinical prediction models developed using supervised machine learning: a systematic review
Background While many studies have consistently found incomplete reporting of regression-
based prediction model studies, evidence is lacking for machine learning-based prediction …
based prediction model studies, evidence is lacking for machine learning-based prediction …
Transparent reporting of multivariable prediction models for individual prognosis or diagnosis: checklist for systematic reviews and meta-analyses (TRIPOD-SRMA)
Most clinical specialties have a plethora of studies that develop or validate one or more
prediction models, for example, to inform diagnosis or prognosis. Having many prediction …
prediction models, for example, to inform diagnosis or prognosis. Having many prediction …
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 …
Introduction The Transparent Reporting of a multivariable prediction model of Individual
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
Prognosis Or Diagnosis (TRIPOD) statement and the Prediction model Risk Of Bias …
[HTML][HTML] Evidence of questionable research practices in clinical prediction models
Background Clinical prediction models are widely used in health and medical research. The
area under the receiver operating characteristic curve (AUC) is a frequently used estimate to …
area under the receiver operating characteristic curve (AUC) is a frequently used estimate to …
[HTML][HTML] External validation of multivariable prediction models: a systematic review of methodological conduct and reporting
GS Collins, JA de Groot, S Dutton, O Omar… - BMC medical research …, 2014 - Springer
Background Before considering whether to use a multivariable (diagnostic or prognostic)
prediction model, it is essential that its performance be evaluated in data that were not used …
prediction model, it is essential that its performance be evaluated in data that were not used …
[HTML][HTML] Reporting and methods in clinical prediction research: a systematic review
W Bouwmeester, NPA Zuithoff, S Mallett… - PLoS …, 2012 - journals.plos.org
Background We investigated the reporting and methods of prediction studies, focusing on
aims, designs, participant selection, outcomes, predictors, statistical power, statistical …
aims, designs, participant selection, outcomes, predictors, statistical power, statistical …
Calculating the sample size required for developing a clinical prediction model
Clinical prediction models aim to predict outcomes in individuals, to inform diagnosis or
prognosis in healthcare. Hundreds of prediction models are published in the medical …
prognosis in healthcare. Hundreds of prediction models are published in the medical …