Literature DB >> 31073858

Evaluation of prostate MRI: can machine learning provide support where radiologists need it?

Alexander D J Baur1, Tobias Penzkofer2,3.   

Abstract

Year:  2019        PMID： 31073858     DOI： 10.1007/s00330-019-06241-5

Source DB:  PubMed          Journal:  Eur Radiol        ISSN： 0938-7994            Impact factor:   5.315


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  9 in total

Review 1.  Diagnostic Performance of Prostate Imaging Reporting and Data System Version 2 for Detection of Prostate Cancer: A Systematic Review and Diagnostic Meta-analysis.

Authors:  Sungmin Woo; Chong Hyun Suh; Sang Youn Kim; Jeong Yeon Cho; Seung Hyup Kim
Journal:  Eur Urol       Date:  2017-02-11       Impact factor: 20.096

Review 2.  Implementing Machine Learning in Radiology Practice and Research.

Authors:  Marc Kohli; Luciano M Prevedello; Ross W Filice; J Raymond Geis
Journal:  AJR Am J Roentgenol       Date:  2017-01-26       Impact factor: 3.959

3.  Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists.

Authors:  Andrew B Rosenkrantz; Luke A Ginocchio; Daniel Cornfeld; Adam T Froemming; Rajan T Gupta; Baris Turkbey; Antonio C Westphalen; James S Babb; Daniel J Margolis
Journal:  Radiology       Date:  2016-04-01       Impact factor: 11.105

4.  Machine learning-based analysis of MR radiomics can help to improve the diagnostic performance of PI-RADS v2 in clinically relevant prostate cancer.

Authors:  Jing Wang; Chen-Jiang Wu; Mei-Ling Bao; Jing Zhang; Xiao-Ning Wang; Yu-Dong Zhang
Journal:  Eur Radiol       Date:  2017-04-03       Impact factor: 5.315

Review 5.  The Emerging Role of MRI in Prostate Cancer Active Surveillance and Ongoing Challenges.

Authors:  Tristan Barrett; Masoom A Haider
Journal:  AJR Am J Roentgenol       Date:  2016-10-11       Impact factor: 3.959

6.  Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions.

Authors:  Anwar R Padhani; Jeffrey Weinreb; Andrew B Rosenkrantz; Geert Villeirs; Baris Turkbey; Jelle Barentsz
Journal:  Eur Urol       Date:  2018-06-13       Impact factor: 20.096

Review 7.  Prostate Imaging Reporting and Data System Version 2.1: 2019 Update of Prostate Imaging Reporting and Data System Version 2.

Authors:  Baris Turkbey; Andrew B Rosenkrantz; Masoom A Haider; Anwar R Padhani; Geert Villeirs; Katarzyna J Macura; Clare M Tempany; Peter L Choyke; Francois Cornud; Daniel J Margolis; Harriet C Thoeny; Sadhna Verma; Jelle Barentsz; Jeffrey C Weinreb
Journal:  Eur Urol       Date:  2019-03-18       Impact factor: 20.096

8.  Diagnostic accuracy of multi-parametric MRI and TRUS biopsy in prostate cancer (PROMIS): a paired validating confirmatory study.

Authors:  Hashim U Ahmed; Ahmed El-Shater Bosaily; Louise C Brown; Rhian Gabe; Richard Kaplan; Mahesh K Parmar; Yolanda Collaco-Moraes; Katie Ward; Richard G Hindley; Alex Freeman; Alex P Kirkham; Robert Oldroyd; Chris Parker; Mark Emberton
Journal:  Lancet       Date:  2017-01-20       Impact factor: 79.321

9.  A Contemporary Prostate Cancer Grading System: A Validated Alternative to the Gleason Score.

Authors:  Jonathan I Epstein; Michael J Zelefsky; Daniel D Sjoberg; Joel B Nelson; Lars Egevad; Cristina Magi-Galluzzi; Andrew J Vickers; Anil V Parwani; Victor E Reuter; Samson W Fine; James A Eastham; Peter Wiklund; Misop Han; Chandana A Reddy; Jay P Ciezki; Tommy Nyberg; Eric A Klein
Journal:  Eur Urol       Date:  2015-07-10       Impact factor: 20.096
  9 in total

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