Literature DB >> 29158061

Machine Learning in Radiology: Applications Beyond Image Interpretation.

Paras Lakhani1, Adam B Prater2, R Kent Hutson3, Kathy P Andriole4, Keith J Dreyer5, Jose Morey6, Luciano M Prevedello7, Toshi J Clark8, J Raymond Geis8, Jason N Itri9, C Matthew Hawkins2.   

Abstract

Much attention has been given to machine learning and its perceived impact in radiology, particularly in light of recent success with image classification in international competitions. However, machine learning is likely to impact radiology outside of image interpretation long before a fully functional "machine radiologist" is implemented in practice. Here, we describe an overview of machine learning, its application to radiology and other domains, and many cases of use that do not involve image interpretation. We hope that better understanding of these potential applications will help radiology practices prepare for the future and realize performance improvement and efficiency gains.
Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; deep learning; machine learning; radiology; workflows

Mesh:

Year:  2017        PMID: 29158061     DOI: 10.1016/j.jacr.2017.09.044

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  42 in total

1.  Point Shear Wave Elastography Using Machine Learning to Differentiate Renal Cell Carcinoma and Angiomyolipoma.

Authors:  Hersh Sagreiya; Alireza Akhbardeh; Dandan Li; Rosa Sigrist; Benjamin I Chung; Geoffrey A Sonn; Lu Tian; Daniel L Rubin; Jürgen K Willmann
Journal:  Ultrasound Med Biol       Date:  2019-05-25       Impact factor: 2.998

Review 2.  Artificial intelligence for precision education in radiology.

Authors:  Michael Tran Duong; Andreas M Rauschecker; Jeffrey D Rudie; Po-Hao Chen; Tessa S Cook; R Nick Bryan; Suyash Mohan
Journal:  Br J Radiol       Date:  2019-07-26       Impact factor: 3.039

3.  Fostering a Healthy AI Ecosystem for Radiology: Conclusions of the 2018 RSNA Summit on AI in Radiology.

Authors:  Falgun H Chokshi; Adam E Flanders; Luciano M Prevedello; Curtis P Langlotz
Journal:  Radiol Artif Intell       Date:  2019-03-27

4.  The Case for User-Centered Artificial Intelligence in Radiology.

Authors:  Ross W Filice; Raj M Ratwani
Journal:  Radiol Artif Intell       Date:  2020-05-13

5.  Artificial Intelligence in Thoracic Radiology. A Challenge in COVID-19 Times?

Authors:  María Dolores Corbacho Abelaira; Alberto Ruano-Ravina; Alberto Fernández-Villar
Journal:  Arch Bronconeumol       Date:  2020-10-22       Impact factor: 4.872

6.  Crowdsourcing pneumothorax annotations using machine learning annotations on the NIH chest X-ray dataset.

Authors:  Ross W Filice; Anouk Stein; Carol C Wu; Veronica A Arteaga; Stephen Borstelmann; Ramya Gaddikeri; Maya Galperin-Aizenberg; Ritu R Gill; Myrna C Godoy; Stephen B Hobbs; Jean Jeudy; Paras C Lakhani; Archana Laroia; Sundeep M Nayak; Maansi R Parekh; Prasanth Prasanna; Palmi Shah; Dharshan Vummidi; Kavitha Yaddanapudi; George Shih
Journal:  J Digit Imaging       Date:  2020-04       Impact factor: 4.056

Review 7.  Artificial intelligence in diagnostic imaging: impact on the radiography profession.

Authors:  Maryann Hardy; Hugh Harvey
Journal:  Br J Radiol       Date:  2019-12-16       Impact factor: 3.039

Review 8.  Artificial Intelligence in Musculoskeletal Imaging: Current Status and Future Directions.

Authors:  Soterios Gyftopoulos; Dana Lin; Florian Knoll; Ankur M Doshi; Tatiane Cantarelli Rodrigues; Michael P Recht
Journal:  AJR Am J Roentgenol       Date:  2019-06-05       Impact factor: 3.959

9.  Potential of a machine-learning model for dose optimization in CT quality assurance.

Authors:  Axel Meineke; Christian Rubbert; Lino M Sawicki; Christoph Thomas; Yan Klosterkemper; Elisabeth Appel; Julian Caspers; Oliver T Bethge; Patric Kröpil; Gerald Antoch; Johannes Boos
Journal:  Eur Radiol       Date:  2019-02-19       Impact factor: 5.315

10.  MRI-guided vacuum-assisted breast biopsy: experience of a single tertiary referral cancer centre and prospects for the future.

Authors:  Silvia Penco; Anna Rotili; Filippo Pesapane; Chiara Trentin; Valeria Dominelli; Angela Faggian; Mariagiorgia Farina; Irene Marinucci; Anna Bozzini; Maria Pizzamiglio; Anna Maria Ierardi; Enrico Cassano
Journal:  Med Oncol       Date:  2020-03-27       Impact factor: 3.064

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