Back to search

Article

Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – changing the way we validate classification algorithms?

2020-08-14

Abstract excerpt

Adoption of Artificial Intelligence (AI) algorithms into the clinical realm will depend on their inherent trustworthiness, which is built not only by robust validation studies but is also deeply linked to the explainability and interpretability of the algorithms. Most validation studies for medical imaging AI report performance of algorithms on study-level labels and lay little emphasis on measuring the accuracy o...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
ef54bd3a-e1e7-527d-bff8-3065933d2c06
DOI
10.1101/2020.08.12.20169607
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – changing the way we validate classification algorithms?DOI 10.1101/2020.08.12.20169607
Select a neighboring publication to make it the new centre.