Literature DB >> 32428437

Artificial Intelligence and Machine Learning in Radiology Education Is Ready for Prime Time.

Priscilla J Slanetz1, Dania Daye2, Po-Hao Chen3, Lonie R Salkowski4.   

Abstract

Mesh：

Year:  2020        PMID： 32428437     DOI： 10.1016/j.jacr.2020.04.022

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


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  4 in total

1.  Natural Language Processing of Radiology Text Reports: Interactive Text Classification.

Authors:  Walter F Wiggins; Felipe Kitamura; Igor Santos; Luciano M Prevedello
Journal:  Radiol Artif Intell       Date:  2021-05-12

2.  Individualized and generalized models for predicting observer performance on liver metastasis detection using CT.

Authors:  Parvathy Sudhir Pillai; David R Holmes; Rickey Carter; Akitoshi Inoue; David A Cook; Ron Karwoski; Jeff L Fidler; Joel G Fletcher; Shuai Leng; Lifeng Yu; Cynthia H McCollough; Scott S Hsieh
Journal:  J Med Imaging (Bellingham)       Date:  2022-09-13

Review 3.  Artificial intelligence in paediatric radiology: Future opportunities.

Authors:  Natasha Davendralingam; Neil J Sebire; Owen J Arthurs; Susan C Shelmerdine
Journal:  Br J Radiol       Date:  2020-09-17       Impact factor: 3.039

4.  A Conference-Friendly, Hands-on Introduction to Deep Learning for Radiology Trainees.

Authors:  Walter F Wiggins; M Travis Caton; Kirti Magudia; Michael H Rosenthal; Katherine P Andriole
Journal:  J Digit Imaging       Date:  2021-07-29       Impact factor: 4.903
  4 in total

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