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...

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Vydáno v:	Journal of medical systems Ročník 46; číslo 4; s. 20
Hlavní autoři:	Venugopal, Vasantha Kumar, Takhar, Rohit, Gupta, Salil, Mahajan, Vidur
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.04.2022 Springer Nature B.V
Témata:	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
On-line přístup:	Získat plný text
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