Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) – Changing the Way We Validate Classification Algorithms

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...

Full description

Saved in:

Bibliographic Details
Published in:	Journal of medical systems Vol. 46; no. 4; p. 20
Main Authors:	Venugopal, Vasantha Kumar, Takhar, Rohit, Gupta, Salil, Mahajan, Vidur
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.04.2022 Springer Nature B.V
Subjects:	Algorithms Artificial Intelligence Chest Classification Consolidation Deep learning Diagnostic Imaging Failure Health Informatics Health Sciences Humans Image & Signal Processing Medical imaging Medicine Medicine & Public Health Radiography Statistical analysis Statistics for Life Sciences Trustworthiness Validation studies X-rays Deep learning Medical imaging Explainable AI AI (Artificial Intelligence)
ISSN:	0148-5598, 1573-689X, 1573-689X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!