Upstream Machine Learning in Radiology-Reference-Cited by-同舟云学术

Upstream Machine Learning in Radiology

Published:2021-11 Issue:6 Volume:59 Page:967-985
ISSN:0033-8389
Container-title:Radiologic Clinics of North America
language:en
Short-container-title:Radiologic Clinics of North America

Author:

Sandino Christopher M.,Cole Elizabeth K.,Alkan Cagan,Chaudhari Akshay S.,Loening Andreas M.,Hyun Dongwoon,Dahl Jeremy,Imran Abdullah-Al-Zubaer,Wang Adam S.,Vasanawala Shreyas S.

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Reference92 articles.

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2. CT and MR protocol standardization across a large health system: providing a consistent radiologist, patient, and referring provider experience;Sachs;J Digit Imaging,2017

3. Machine learning for automation of radiology protocols for quality and efficiency improvement;Kalra;J Am Coll Radiol,2020

4. Efficiency improvement in a busy radiology practice: determination of musculoskeletal magnetic resonance imaging protocol using deep-learning convolutional neural networks;Lee;J Digit Imaging,2018

5. Automatic determination of the need for intravenous contrast in musculoskeletal MRI examinations using IBM Watson's Natural Language Processing Algorithm;Trivedi;J Digit Imaging,2018

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