Machine learning concepts, concerns and opportunities for a pediatric radiologist.

Moore, Michael M; Slonimsky, Einat; Long, Aaron D; Sze, Raymond W; Iyer, Ramesh S

Moore, Michael M; Slonimsky, Einat; Long, Aaron D; Sze, Raymond W; Iyer, Ramesh S.

Affiliation

Moore MM; Department of Radiology, Penn State Health, Mail Code H066, 500 University Drive, P.O. Box 850, Hershey, PA, 17033-0850, USA. mmoore5@pennstatehealth.psu.edu.
Slonimsky E; Department of Radiology, Penn State Health, Mail Code H066, 500 University Drive, P.O. Box 850, Hershey, PA, 17033-0850, USA.
Long AD; Department of Radiology, Penn State Health, Mail Code H066, 500 University Drive, P.O. Box 850, Hershey, PA, 17033-0850, USA.
Sze RW; Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Iyer RS; Department of Radiology, Seattle Children's Hospital, Seattle, WA, USA.

Pediatr Radiol ; 49(4): 509-516, 2019 04.

Article in En | MEDLINE | ID: mdl-30923883

Subject(s)

Diagnostic Errors/prevention & control; Machine Learning; Patient Safety; Pediatrics/methods; Quality Improvement; Radiology/methods; Humans; Societies, Medical

Key words

Convolution neural network; Labeling; Machine learning; Overfitting; Pediatric radiology; Semisupervised learning

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Pediatrics / Radiology / Diagnostic Errors / Quality Improvement / Patient Safety / Machine Learning Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Pediatr Radiol Year: 2019 Document type: Article Affiliation country: United States Country of publication: Germany

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