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Better AI for Kids: Learning from the AI-OPiNE Study.

作者信息

Rafful Patricia P, Reis Teixeira Sara

机构信息

From the Children's Hospital of Philadelphia, 3401 Civic Center Blvd, Philadelphia, PA 19104.

出版信息

Radiol Artif Intell. 2024 Sep;6(5):e240376. doi: 10.1148/ryai.240376.

Abstract
摘要

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本文引用的文献

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Artificial Intelligence Outcome Prediction in Neonates with Encephalopathy (AI-OPiNE).
Radiol Artif Intell. 2024 Sep;6(5):e240076. doi: 10.1148/ryai.240076.
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Checklist for Artificial Intelligence in Medical Imaging (CLAIM): 2024 Update.
Radiol Artif Intell. 2024 Jul;6(4):e240300. doi: 10.1148/ryai.240300.
3
Quantifying Uncertainty in Deep Learning of Radiologic Images.
Radiology. 2023 Aug;308(2):e222217. doi: 10.1148/radiol.222217.
4
How well does neonatal neuroimaging correlate with neurodevelopmental outcomes in infants with hypoxic-ischemic encephalopathy?
Pediatr Res. 2023 Sep;94(3):1018-1025. doi: 10.1038/s41390-023-02510-8. Epub 2023 Mar 1.
5
Federated Learning in Medical Imaging: Part II: Methods, Challenges, and Considerations.
J Am Coll Radiol. 2022 Aug;19(8):975-982. doi: 10.1016/j.jacr.2022.03.016. Epub 2022 Apr 25.
6
Magician's Corner: 9. Performance Metrics for Machine Learning Models.
Radiol Artif Intell. 2021 May 12;3(3):e200126. doi: 10.1148/ryai.2021200126. eCollection 2021 May.
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Preparing Medical Imaging Data for Machine Learning.
Radiology. 2020 Apr;295(1):4-15. doi: 10.1148/radiol.2020192224. Epub 2020 Feb 18.
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A validated clinical MRI injury scoring system in neonatal hypoxic-ischemic encephalopathy.
Pediatr Radiol. 2017 Oct;47(11):1491-1499. doi: 10.1007/s00247-017-3893-y. Epub 2017 Jun 16.

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