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The IJMEDI checklist for assessment of medical AI

appsOther research productkeyboard_double_arrow_right Other ORP type , Other literature type 28 May 2021Publisher:Zenodo
Authors: Cabitza, Federico; Campagner, Andrea;

doi: 10.5281/zenodo.4835800 , 10.5281/zenodo.5604495 , 10.5281/zenodo.4835799 , 10.5281/zenodo.6451243

The IJMEDI checklist for assessment of medical AI

Abstract

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. This checklist is licensed under a Creative Commons “Attribution-ShareAlike 4.0International” license. If you want to cite this checklist: Cabitza F., Campagner, A. (2021) The need to separate the wheat from the chaff in medical informatics. International Journal of Medical Informatics.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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