Literature DB >> 34056592

Artificial Intelligence for Breast Ultrasound: Will It Impact Radiologists' Accuracy?

Manisha Bahl1.   

Abstract

Entities:  

Keywords:  artificial intelligence; breast density; deep learning; reader study; screening ultrasound

Year:  2021        PMID： 34056592      PMCID： PMC8139610          DOI： 10.1093/jbi/wbab022

Source DB:  PubMed          Journal:  J Breast Imaging        ISSN： 2631-6110


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  14 in total

1.  Detecting Breast Cancers with Mammography: Will AI Succeed Where Traditional CAD Failed?

Authors:  Manisha Bahl
Journal:  Radiology       Date:  2018-11-20       Impact factor: 11.105

2.  One step further into the blackbox: a pilot study of how to build more confidence around an AI-based decision system of breast nodule assessment in 2D ultrasound.

Authors:  Fajin Dong; Ruilian She; Chen Cui; Siyuan Shi; Xuqiao Hu; Jieying Zeng; Huaiyu Wu; Jinfeng Xu; Yun Zhang
Journal:  Eur Radiol       Date:  2021-01-06       Impact factor: 5.315

3.  Screening Breast Ultrasound: Update After 10 Years of Breast Density Notification Laws.

Authors:  Reni S Butler; Regina J Hooley
Journal:  AJR Am J Roentgenol       Date:  2020-03-17       Impact factor: 3.959

Review 4.  Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology.

Authors:  An Tang; Roger Tam; Alexandre Cadrin-Chênevert; Will Guest; Jaron Chong; Joseph Barfett; Leonid Chepelev; Robyn Cairns; J Ross Mitchell; Mark D Cicero; Manuel Gaudreau Poudrette; Jacob L Jaremko; Caroline Reinhold; Benoit Gallix; Bruce Gray; Raym Geis
Journal:  Can Assoc Radiol J       Date:  2018-04-11       Impact factor: 2.248

5.  Can an Artificial Intelligence Decision Aid Decrease False-Positive Breast Biopsies?

Authors:  Samantha L Heller; Melanie Wegener; James S Babb; Yiming Gao
Journal:  Ultrasound Q       Date:  2020-12-28       Impact factor: 1.657

Review 6.  Screening breast ultrasound: past, present, and future.

Authors:  Rachel F Brem; Megan J Lenihan; Jennifer Lieberman; Jessica Torrente
Journal:  AJR Am J Roentgenol       Date:  2015-02       Impact factor: 3.959

Review 7.  Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.

Authors:  Krzysztof J Geras; Ritse M Mann; Linda Moy
Journal:  Radiology       Date:  2019-09-24       Impact factor: 11.105

8.  Using Time as a Measure of Impact for AI Systems: Implications in Breast Screening.

Authors:  William Hsu; Anne C Hoyt
Journal:  Radiol Artif Intell       Date:  2019-07-31

9.  Impact of Data Presentation on Physician Performance Utilizing Artificial Intelligence-Based Computer-Aided Diagnosis and Decision Support Systems.

Authors:  L Barinov; A Jairaj; M Becker; S Seymour; E Lee; A Schram; E Lane; A Goldszal; D Quigley; L Paster
Journal:  J Digit Imaging       Date:  2019-06       Impact factor: 4.056

10.  Deep learning-based computer-aided diagnosis in screening breast ultrasound to reduce false-positive diagnoses.

Authors:  Soo -Yeon Kim; Yunhee Choi; Eun -Kyung Kim; Boo-Kyung Han; Jung Hyun Yoon; Ji Soo Choi; Jung Min Chang
Journal:  Sci Rep       Date:  2021-01-11       Impact factor: 4.379
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  1 in total

Review 1.  Updates in Artificial Intelligence for Breast Imaging.

Authors:  Manisha Bahl
Journal:  Semin Roentgenol       Date:  2021-12-31       Impact factor: 0.709
  1 in total

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