A survey of recent methods for addressing AI fairness and bias in biomedicine-Reference-Cited by-同舟云学术

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A survey of recent methods for addressing AI fairness and bias in biomedicine

Published:2024-06 Issue: Volume:154 Page:104646
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Yang Yifan^ORCID,Lin Mingquan,Zhao Han,Peng Yifan,Huang Furong,Lu Zhiyong^ORCID

Funder

U.S. National Library of Medicine

NIH

Publisher

Elsevier BV

Reference96 articles.

1. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis;Liu;Lancet Digit. Health,2019

2. Addressing bias: artificial intelligence in cardiovascular medicine;Tat;Lancet Digit. Health,2020

3. Addressing fairness in artificial intelligence for medical imaging;Ricci Lara;Nat. Commun.,2022

4. Artificial intelligence in ophthalmology: a meta-analysis of deep learning models for retinal vessels segmentation;Islam;J. Clin. Med.,2020

5. Clinical applications of machine learning algorithms: beyond the black box;Watson;BMJ,2019

Cited by 2 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. Large language models in biomedicine and health: current research landscape and future directions;Journal of the American Medical Informatics Association;2024-08-22

2. Factors associated with prognosis and staging of intrahepatic cholangiocarcinoma;Journal of Cancer Metastasis and Treatment;2024-07-10

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