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Deep learning and artificial intelligence in radiology: Current applications and future directions

2018·226 Zitationen·PLoS MedicineOpen Access
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226

Zitationen

2

Autoren

2018

Jahr

Abstract

Radiological imaging diagnosis plays important roles in clinical patient management. Deep learning with convolutional neural networks (CNNs) is recently gaining wide attention for its high performance in recognizing images. If CNNs realize their promise in the context of radiology, they are anticipated to help radiologists achieve diagnostic excellence and to enhance patient healthcare. Here, we discuss very recent developments in the field, including studies published in the current PLOS Medicine Special Issue on Machine Learning in Health and Biomedicine, with comment on expectations and planning for artificial intelligence (AI) in the radiology clinic.

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Autoren

Institutionen

Themen

Radiomics and Machine Learning in Medical ImagingArtificial Intelligence in Healthcare and EducationMedical Imaging and Analysis
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