Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a sco** review

AAH de Hond, AM Leeuwenberg, L Hooft… - NPJ digital …, 2022‏ - nature.com
While the opportunities of ML and AI in healthcare are promising, the growth of complex data-
driven prediction models requires careful quality and applicability assessment before they …

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

L Wynants, B Van Calster, GS Collins, RD Riley… - bmj, 2020‏ - bmj.com
Objective To review and appraise the validity and usefulness of published and preprint
reports of prediction models for prognosis of patients with covid-19, and for detecting people …

There is no such thing as a validated prediction model

B Van Calster, EW Steyerberg, L Wynants… - BMC medicine, 2023‏ - Springer
Background Clinical prediction models should be validated before implementation in clinical
practice. But is favorable performance at internal validation or one external validation …

Criteria for the translation of radiomics into clinically useful tests

EP Huang, JPB O'Connor, LM McShane… - Nature reviews Clinical …, 2023‏ - nature.com
Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …

Illusory generalizability of clinical prediction models

AM Chekroud, M Hawrilenko, H Loho, J Bondar… - Science, 2024‏ - science.org
It is widely hoped that statistical models can improve decision-making related to medical
treatments. Because of the cost and scarcity of medical outcomes data, this hope is typically …

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease

M Van Smeden, G Heinze, B Van Calster… - European heart …, 2022‏ - academic.oup.com
The medical field has seen a rapid increase in the development of artificial intelligence (AI)-
based prediction models. With the introduction of such AI-based prediction model tools and …

The importance of being external. methodological insights for the external validation of machine learning models in medicine

F Cabitza, A Campagner, F Soares… - Computer Methods and …, 2021‏ - Elsevier
Abstract Background and Objective Medical machine learning (ML) models tend to perform
better on data from the same cohort than on new data, often due to overfitting, or co-variate …

Methodological guidance for the evaluation and updating of clinical prediction models: a systematic review

MAE Binuya, EG Engelhardt, W Schats… - BMC Medical Research …, 2022‏ - Springer
Background Clinical prediction models are often not evaluated properly in specific settings
or updated, for instance, with information from new markers. These key steps are needed …

TRIPOD+ AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods

GS Collins, KGM Moons, P Dhiman, RD Riley… - bmj, 2024‏ - bmj.com
The TRIPOD (Transparent Reporting of a multivariable prediction model for Individual
Prognosis Or Diagnosis) statement was published in 2015 to provide the minimum reporting …

Continual updating and monitoring of clinical prediction models: time for dynamic prediction systems?

DA Jenkins, GP Martin, M Sperrin, RD Riley… - Diagnostic and …, 2021‏ - Springer
Clinical prediction models (CPMs) have become fundamental for risk stratification across
healthcare. The CPM pipeline (development, validation, deployment, and impact …