A Survey of Bias and Fairness in Healthcare AI

被引：1
作者：
Mienye, Lbomoiye Domor [1 ]
Obaido, George [2 ]
Emmanuel, Ikiomoye Douglas [3 ]
Ajani, Ayodeji Akeem [4 ]
机构：
[1] Walter Sisulu Univ, Dept Informat Technol, Buffalo City Campus, ZA-5200 East London, South Africa
[2] Univ Calif Berkeley, Berkeley Inst Data Sci BIDS, Ctr Human Compatible Artificial Intelligence CHAI, Berkeley, CA 94720 USA
[3] Univ Salford, Sch Sci Engn & Environm, Salford, Lancs, England
[4] Global Banking Sch, Manchester M12 6JH, Lancs, England
来源：
2024 IEEE 12TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS, ICHI 2024 | 2024年
关键词：
artificial intelligence; bias; ethics; fairness; healthcare; machine learning;
D O I：
10.1109/ICHI61247.2024.00103
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The integration of artificial intelligence (AI) technologies in healthcare has shown great promise in improving patient outcomes. However, there have been concerns about bias and ethical implications. This review explores the key issues of bias, fairness, and ethical considerations in healthcare AI. The review provides a foundation for future research and policy development in the field of healthcare AI. It will be beneficial to researchers, policymakers, healthcare providers, and technology developers who are involved in the development of AI systems in healthcare.
引用
收藏
页码：642 / 650
页数：9
相关论文
共 65 条
  • [1] Big healthcare data: preserving security and privacy
    Abouelmehdi, Karim
    Beni-Hessane, Abderrahim
    Khaloufi, Hayat
    [J]. JOURNAL OF BIG DATA, 2018, 5 (01)
  • [2] The Artificial Intelligence Revolution in Digital Finance in Saudi Arabia: A Comprehensive Review and Proposed Framework
    Al-Baity, Heyam H.
    [J]. SUSTAINABILITY, 2023, 15 (18)
  • [3] Explainable AI for Retinoblastoma Diagnosis: Interpreting Deep Learning Models with LIME and SHAP
    Aldughayfiq, Bader
    Ashfaq, Farzeen
    Jhanjhi, N. Z.
    Humayun, Mamoona
    [J]. DIAGNOSTICS, 2023, 13 (11)
  • [4] AI, big data, and the future of consent
    Andreotta, Adam J.
    Kirkham, Nin
    Rizzi, Marco
    [J]. AI & SOCIETY, 2022, 37 (04) : 1715 - 1728
  • [5] Transparency and Explainability of AI Systems: Ethical Guidelines in Practice
    Balasubramaniam, Nagadivya
    Kauppinen, Marjo
    Hiekkanen, Kari
    Kujala, Sari
    [J]. REQUIREMENTS ENGINEERING: FOUNDATION FOR SOFTWARE QUALITY, REFSQ 2022, 2022, 13216 : 3 - 18
  • [6] The Role of AI in Drug Discovery: Challenges, Opportunities, and Strategies
    Blanco-Gonzalez, Alexandre
    Cabezon, Alfonso
    Seco-Gonzalez, Alejandro
    Conde-Torres, Daniel
    Antelo-Riveiro, Paula
    Pineiro, Angel
    Garcia-Fandino, Rebeca
    [J]. PHARMACEUTICALS, 2023, 16 (06)
  • [7] Artificial Intelligence in Skin Cancer Diagnosis: A Reality Check
    Brancaccio, Gabriella
    Balato, Anna
    Malvehy, Josep
    Puig, Susana
    Argenziano, Giuseppe
    Kittler, Harald
    [J]. JOURNAL OF INVESTIGATIVE DERMATOLOGY, 2024, 144 (03) : 492 - 499
  • [8] To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-making
    Buçinca Z.
    Malaya M.B.
    Gajos K.Z.
    [J]. Proceedings of the ACM on Human-Computer Interaction, 2021, 5 (CSCW1)
  • [9] Caton S., 2020, ACM Computing Surveys
  • [10] Fragmentation and the Future: Investigating Architectures for International AI Governance
    Cihon, Peter
    Maas, Matthijs M.
    Kemp, Luke
    [J]. GLOBAL POLICY, 2020, 11 (05) : 545 - 556
1234567