Clinician feedback on the design features of an AI tool to identify Fabry disease

This paper presents feedback from a focus group of cardiologists (n=6) regarding an AI tool to assist in the identification of Fabry disease. The key feedback on the features, explainability and its role in clinical workflow are explored.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-09-04
DOI
https://doi.org/10.5281/zenodo.13152404
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00
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article

Clinician feedback on the design features of an AI tool to identify Fabry disease

Zenodo (CERN European Organization for Nuclear Research)
Genomics and Rare Diseases
article

Clinician feedback on the design features of an AI tool to identify Fabry disease

article en

Abstract

This paper presents feedback from a focus group of cardiologists (n=6) regarding an AI tool to assist in the identification of Fabry disease. The key feedback on the features, explainability and its role in clinical workflow are explored.

Zenodo (CERN European Organization for Nuclear Research)
Cardiff University (GB)
Openalex Percentile: Top 54%
Genomics and Rare Diseases
DOIOpen Access PDFOpenAlex
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Clinician feedback on the design features of an AI tool to identify Fabry disease · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS