Artificial Intelligence in Radiology: Opportunities and Challenges

Artificial Intelligence in Radiology: Opportunities and Challenges

Artificial intelligence’s (AI) emergence in radiology elicits both excitement and uncertainty. AI holds promise for improving radiology with regards to clinical practice, education, and research opportunities. Yet, AI systems are trained on select datasets that can contain bias and inaccuracies. Rad...

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Veröffentlicht in:Seminars in ultrasound, CT, and MRI CT, and MRI, 2024-04, Vol.45 (2), p.152-160
Hauptverfasser: Flory, Marta N., Napel, Sandy, Tsai, Emily B.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Artificial Intelligence
Diagnostic Imaging - methods
Humans
Radiology - methods
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Zusammenfassung:Artificial intelligence’s (AI) emergence in radiology elicits both excitement and uncertainty. AI holds promise for improving radiology with regards to clinical practice, education, and research opportunities. Yet, AI systems are trained on select datasets that can contain bias and inaccuracies. Radiologists must understand these limitations and engage with AI developers at every step of the process – from algorithm initiation and design to development and implementation – to maximize benefit and minimize harm that can be enabled by this technology.
ISSN:0887-2171
1558-5034
1558-5034
DOI:10.1053/j.sult.2024.02.004