Hurdles to Artificial Intelligence Deployment: Noise in Schemas and “Gold” Labels-Reference-Cited by-同舟云学术

Hurdles to Artificial Intelligence Deployment: Noise in Schemas and “Gold” Labels

Published:2023-03-01 Issue:2 Volume:5 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Abdalla Mohamed¹^ORCID,Fine Benjamin¹^ORCID

Affiliation:

1. From the Institute for Better Health, Trillium Health Partners, Mississauga, Ontario, Canada (M.A., B.F.); and Centre for Information Technology, Department of Computer Science (M.A.), and Department of Medical Imaging (B.F.), University of Toronto, 40 St George St, Room 4283, Toronto, ON, Canada M5S 2E4.

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.220056

Reference22 articles.

1. Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists

2. Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels

3. Artificial Intelligence and Human Trust in Healthcare: Focus on Clinicians

4. Informatics in Radiology: Radiology Gamuts Ontology: Differential Diagnosis for the Semantic Web

5. CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison

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