Literature DB >> 31005452

Why Radiologists Have Nothing to Fear From Deep Learning.

Alex Bratt.   

Abstract

Year:  2019        PMID： 31005452     DOI： 10.1016/j.jacr.2019.02.037

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


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  3 in total

Review 1.  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

2.  Elaboration and Validation of a Nomogram Based on Axillary Ultrasound and Tumor Clinicopathological Features to Predict Axillary Lymph Node Metastasis in Patients With Breast Cancer.

Authors:  Yubo Liu; Feng Ye; Yun Wang; Xueyi Zheng; Yini Huang; Jianhua Zhou
Journal:  Front Oncol       Date:  2022-05-16       Impact factor: 5.738

3.  Diagnostic study on clinical feasibility of an AI-based diagnostic system as a second reader on mobile CT images: a preliminary result.

Authors:  Kaiyue Diao; Yuntian Chen; Ying Liu; Bo-Jiang Chen; Wan-Jiang Li; Lin Zhang; Ya-Li Qu; Tong Zhang; Yun Zhang; Min Wu; Kang Li; Bin Song
Journal:  Ann Transl Med       Date:  2022-06
  3 in total

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