Literature DB >> 35576821

Explainable artificial intelligence (XAI) in deep learning-based medical image analysis.

Bas H M van der Velden1, Hugo J Kuijf2, Kenneth G A Gilhuijs2, Max A Viergever2.   

Abstract

With an increase in deep learning-based methods, the call for explainability of such methods grows, especially in high-stakes decision making areas such as medical image analysis. This survey presents an overview of explainable artificial intelligence (XAI) used in deep learning-based medical image analysis. A framework of XAI criteria is introduced to classify deep learning-based medical image analysis methods. Papers on XAI techniques in medical image analysis are then surveyed and categorized according to the framework and according to anatomical location. The paper concludes with an outlook of future opportunities for XAI in medical image analysis.
Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Deep learning; Explainable artificial intelligence; Interpretable deep learning; Medical image analysis; Survey

Mesh:

Year:  2022        PMID: 35576821     DOI: 10.1016/j.media.2022.102470

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  4 in total

1.  Impact of artificial intelligence on pathologists' decisions: an experiment.

Authors:  Julien Meyer; April Khademi; Bernard Têtu; Wencui Han; Pria Nippak; David Remisch
Journal:  J Am Med Inform Assoc       Date:  2022-09-12       Impact factor: 7.942

Review 2.  Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review.

Authors:  Haomin Chen; Catalina Gomez; Chien-Ming Huang; Mathias Unberath
Journal:  NPJ Digit Med       Date:  2022-10-19

3.  Human-Centered Explainable Artificial Intelligence: Automotive Occupational Health Protection Profiles in Prevention Musculoskeletal Symptoms.

Authors:  Nafiseh Mollaei; Carlos Fujao; Luis Silva; Joao Rodrigues; Catia Cepeda; Hugo Gamboa
Journal:  Int J Environ Res Public Health       Date:  2022-08-03       Impact factor: 4.614

Review 4.  Applying artificial intelligence technology to assist with breast cancer diagnosis and prognosis prediction.

Authors:  Meredith A Jones; Warid Islam; Rozwat Faiz; Xuxin Chen; Bin Zheng
Journal:  Front Oncol       Date:  2022-08-31       Impact factor: 5.738

  4 in total

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