Literature DB >> 29398492

Artificial Intelligence and Radiology: Collaboration Is Key.

Paul H Yi1, Ferdinand K Hui2, Daniel S W Ting3.   

Abstract

Mesh:

Year:  2018        PMID: 29398492     DOI: 10.1016/j.jacr.2017.12.037

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


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  5 in total

1.  Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.

Authors:  Tae Kyung Kim; Paul H Yi; Jinchi Wei; Ji Won Shin; Gregory Hager; Ferdinand K Hui; Haris I Sair; Cheng Ting Lin
Journal:  J Digit Imaging       Date:  2019-12       Impact factor: 4.056

Review 2.  Stakeholders' perspectives on the future of artificial intelligence in radiology: a scoping review.

Authors:  Ling Yang; Ioana Cezara Ene; Reza Arabi Belaghi; David Koff; Nina Stein; Pasqualina Lina Santaguida
Journal:  Eur Radiol       Date:  2021-09-21       Impact factor: 5.315

3.  Web-based study on Chinese dermatologists' attitudes towards artificial intelligence.

Authors:  Changbing Shen; Chengxu Li; Feng Xu; Ziyi Wang; Xue Shen; Jing Gao; Randy Ko; Yan Jing; Xiaofeng Tang; Ruixing Yu; Junhu Guo; Feng Xu; Rusong Meng; Yong Cui
Journal:  Ann Transl Med       Date:  2020-06

Review 4.  Artificial intelligence as a medical device in radiology: ethical and regulatory issues in Europe and the United States.

Authors:  Filippo Pesapane; Caterina Volonté; Marina Codari; Francesco Sardanelli
Journal:  Insights Imaging       Date:  2018-08-15

Review 5.  Applications of artificial intelligence and deep learning in molecular imaging and radiotherapy.

Authors:  Hossein Arabi; Habib Zaidi
Journal:  Eur J Hybrid Imaging       Date:  2020-09-23
  5 in total

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