Literature DB >> 35339253

A No-Math Primer on the Principles of Machine Learning for Radiologists.

Matthew D Lee1, Mohammed Elsayed1, Sumit Chopra2, Yvonne W Lui3.   

Abstract

Machine learning is becoming increasingly important in both research and clinical applications in radiology due to recent technological developments, particularly in deep learning. As these technologies are translated toward clinical practice, there is a need for radiologists and radiology trainees to understand the basic principles behind them. This primer provides an accessible introduction to the vocabulary and concepts that are central to machine learning and relevant to the radiologist.
Copyright © 2022 Elsevier Inc. All rights reserved.

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Year:  2022        PMID: 35339253      PMCID: PMC9363000          DOI: 10.1053/j.sult.2022.02.002

Source DB:  PubMed          Journal:  Semin Ultrasound CT MR        ISSN: 0887-2171            Impact factor:   1.641


  29 in total

1.  Differentiation between treatment-related changes and progressive disease in patients with high grade brain tumors using support vector machine classification based on DCE MRI.

Authors:  Moran Artzi; Gilad Liberman; Guy Nadav; Deborah T Blumenthal; Felix Bokstein; Orna Aizenstein; Dafna Ben Bashat
Journal:  J Neurooncol       Date:  2016-01-11       Impact factor: 4.130

2.  Training a neural network for Gibbs and noise removal in diffusion MRI.

Authors:  Matthew J Muckley; Benjamin Ades-Aron; Antonios Papaioannou; Gregory Lemberskiy; Eddy Solomon; Yvonne W Lui; Daniel K Sodickson; Els Fieremans; Dmitry S Novikov; Florian Knoll
Journal:  Magn Reson Med       Date:  2020-07-14       Impact factor: 4.668

3.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

4.  Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks.

Authors:  D H Kim; T MacKinnon
Journal:  Clin Radiol       Date:  2017-12-18       Impact factor: 2.350

5.  Integrating artificial intelligence into the clinical practice of radiology: challenges and recommendations.

Authors:  Michael P Recht; Marc Dewey; Keith Dreyer; Curtis Langlotz; Wiro Niessen; Barbara Prainsack; John J Smith
Journal:  Eur Radiol       Date:  2020-02-17       Impact factor: 5.315

Review 6.  Artificial Intelligence Explained for Nonexperts.

Authors:  Narges Razavian; Florian Knoll; Krzysztof J Geras
Journal:  Semin Musculoskelet Radiol       Date:  2020-01-28       Impact factor: 1.777

7.  Dermatologist-level classification of skin cancer with deep neural networks.

Authors:  Andre Esteva; Brett Kuprel; Roberto A Novoa; Justin Ko; Susan M Swetter; Helen M Blau; Sebastian Thrun
Journal:  Nature       Date:  2017-01-25       Impact factor: 49.962

8.  A fully automated artificial intelligence method for non-invasive, imaging-based identification of genetic alterations in glioblastomas.

Authors:  Evan Calabrese; Javier E Villanueva-Meyer; Soonmee Cha
Journal:  Sci Rep       Date:  2020-07-16       Impact factor: 4.379

9.  Automated Radiology Alert System for Pneumothorax Detection on Chest Radiographs Improves Efficiency and Diagnostic Performance.

Authors:  Cheng-Yi Kao; Chiao-Yun Lin; Cheng-Chen Chao; Han-Sheng Huang; Hsing-Yu Lee; Chia-Ming Chang; Kang Sung; Ting-Rong Chen; Po-Chang Chiang; Li-Ting Huang; Bow Wang; Yi-Sheng Liu; Jung-Hsien Chiang; Chien-Kuo Wang; Yi-Shan Tsai
Journal:  Diagnostics (Basel)       Date:  2021-06-29

Review 10.  The future of digital health with federated learning.

Authors:  Nicola Rieke; Jonny Hancox; Wenqi Li; Fausto Milletarì; Holger R Roth; Shadi Albarqouni; Spyridon Bakas; Mathieu N Galtier; Bennett A Landman; Klaus Maier-Hein; Sébastien Ourselin; Micah Sheller; Ronald M Summers; Andrew Trask; Daguang Xu; Maximilian Baust; M Jorge Cardoso
Journal:  NPJ Digit Med       Date:  2020-09-14
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