The need to separate the wheat from the chaff in medical informatics: Introducing a comprehensive checklist for the (self)-assessment of medical AI studies.

International Journal of Medical Informatics
Federico Cabitza, Andrea Campagner

Abstract

This editorial aims to contribute to the current debate about the quality of studies that apply machine learning (ML) methodologies to medical data to extract value from them and provide clinicians with viable and useful tools supporting everyday care practices. We propose a practical checklist to help authors to self assess the quality of their contribution and to help reviewers to recognize and appreciate high-quality medical ML studies by distinguishing them from the mere application of ML techniques to medical data.

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Citations

Aug 6, 2021·Computer Methods and Programs in Biomedicine·Federico CabitzaAnna Carobene
Oct 14, 2021·BMJ Health & Care Informatics·Sandeep ReddyBlair Kelly
Nov 4, 2021·Journal of Medical Systems·Luis OalaThomas Wiegand

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