Interpretable Artificial Intelligence: Why and When

被引:31
|
作者
Ghosh, Adarsh [1 ]
Kandasamy, Devasenathipathy [1 ]
机构
[1] All India Inst Med Sci, Dept Radiodiag, New Delhi, India
关键词
biomedical research; deep learning; machine learning;
D O I
10.2214/AJR.19.22145
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
OBJECTIVE. The purpose of this article is to discuss the problem of interpretability of artificial intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms to deal with medical big data. CONCLUSION. A plethora of AI algorithms are currently being used in medical research, but the opacity of these algorithms makes their clinical implementation a dilemma. Clinical decision making cannot be assigned to something that we do not understand. Therefore, AI research should not be limited to reporting accuracy and sensitivity but, rather, should try to explain the underlying reasons for the predictions, in an attempt to enrich biologic understanding and knowledge.
引用
收藏
页码:1137 / 1138
页数:2
相关论文
共 50 条
  • [1] Artificial Neural Networks in Agriculture, the core of artificial intelligence: What, When, and Why
    Castillo-Girones, Salvador
    Munera, Sandra
    Martinez-Sober, Marcelino
    Blasco, Jose
    Cubero, Sergio
    Gomez-Sanchis, Juan
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2025, 230
  • [2] A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
    Bharati S.
    Mondal M.R.H.
    Podder P.
    IEEE Transactions on Artificial Intelligence, 2024, 5 (04): : 1429 - 1442
  • [3] A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
    Bharati, Subrato
    Mondal, M. Rubaiyat Hossain
    Podder, Prajoy
    arXiv, 2023,
  • [4] Application of Artificial Intelligence in Healthcare: The Need for More Interpretable Artificial Intelligence
    Tavares, Jorge
    ACTA MEDICA PORTUGUESA, 2024, 37 (06) : 411 - 414
  • [5] Should artificial intelligence be interpretable to humans?
    Schwartz, Matthew D.
    NATURE REVIEWS PHYSICS, 2022, 4 (12) : 741 - 742
  • [6] The Virtues of Interpretable Medical Artificial Intelligence
    Hatherley, Joshua
    Sparrow, Robert
    Howard, Mark
    CAMBRIDGE QUARTERLY OF HEALTHCARE ETHICS, 2022,
  • [7] Towards 'interpretable' artificial intelligence for dermatology
    Rotemberg, V.
    Halpern, A.
    BRITISH JOURNAL OF DERMATOLOGY, 2019, 181 (01) : 5 - 6
  • [8] Should artificial intelligence be interpretable to humans?
    Matthew D. Schwartz
    Nature Reviews Physics, 2022, 4 : 741 - 742
  • [9] Interpretable Hyperspectral Artificial Intelligence: When nonconvex modeling meets hyperspectral remote sensing
    Hong, Danfeng
    He, Wei
    Yokoya, Naoto
    Yao, Jing
    Gao, Lianru
    Zhang, Liangpei
    Chanussot, Jocelyn
    Zhu, Xiaoxiang
    IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, 2021, 9 (02) : 52 - 87
  • [10] Randomized Clinical Trials of Artificial Intelligence in Medicine: Why, When, and How?
    Park, Seong Ho
    Choi, Joon-Il
    Fournier, Laure
    Vasey, Baptiste
    KOREAN JOURNAL OF RADIOLOGY, 2022, 23 (12) : 1119 - 1125