Artificial intelligence and explanation: How, why, and when to explain black boxes-Reference-Cited by-同舟云学术

Artificial intelligence and explanation: How, why, and when to explain black boxes

Published:2024-04 Issue: Volume:173 Page:111393
ISSN:0720-048X
Container-title:European Journal of Radiology
language:en
Short-container-title:European Journal of Radiology

Author:

Marcus Eric^ORCID,Teuwen Jonas

Funder

KWF Kankerbestrijding

Netherlands Ministry of Health Welfare and Sport

Publisher

Elsevier BV

Reference45 articles.

1. Artificial intelligence in radiology;Hosny;Nat. Rev. Cancer,2018

2. Artificial intelligence and machine learning in radiology: opportunities, challenges, pitfalls, and criteria for success;Thrall;J. Am. Coll. Radiol.,2018

3. Multiparametric MRI of the breast: a review;Marino;J. Magn. Reson. Imaging,2018

4. Artificial intelligence-enhanced breast MRI: applications in breast cancer primary treatment response assessment and prediction;Lo Gullo;Invest. Radiol.,2023

5. Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE);Kelly;Eur. Radiol.,2022

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Artificial intelligence in Ultrasound: Pearls and pitfalls in 2024;Ultraschall in der Medizin - European Journal of Ultrasound;2024-09-06

2. Flood Susceptibility Assessment in Urban Areas via Deep Neural Network Approach;Sustainability;2024-08-29

3. Potential strength and weakness of artificial intelligence integration in emergency radiology: a review of diagnostic utilizations and applications in patient care optimization;Emergency Radiology;2024-08-27

4. Cutting through the hype: the true economic impact and ROI of AI in radiology;European Radiology;2024-06-26

5. Seeing between Time: Higher Frame Rate Cardiac Cine MRI using Deep Learning;Radiology: Cardiothoracic Imaging;2024-06-01