Rajaraman Sivaramakrishnan, Zamzmi Ghada, Yang Feng, Xue Zhiyun, Antani Sameer K
Computational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda MD 20894, USA.
Recent Trends Image Process Pattern Recogn (2022). 2023;1704:3-11. doi: 10.1007/978-3-031-23599-3_1. Epub 2023 Jan 11.
Research in Artificial Intelligence (AI)-based medical computer vision algorithms bear promises to improve disease screening, diagnosis, and subsequently patient care. However, these algorithms are highly impacted by the characteristics of the underlying data. In this work, we discuss various data characteristics, namely , and that impact the design, reliability, and evolution of machine learning in medical computer vision. Further, we discuss each characteristic and the recent works conducted in our research lab that informed our understanding of the impact of these characteristics on the design of medical decision-making algorithms and outcome reliability.
基于人工智能（AI）的医学计算机视觉算法的研究有望改善疾病筛查、诊断以及后续的患者护理。然而，这些算法受到基础数据特征的极大影响。在这项工作中，我们讨论了各种数据特征，即[此处原文缺失具体特征内容]，这些特征会影响医学计算机视觉中机器学习的设计、可靠性和发展。此外，我们还讨论了每个特征以及我们研究实验室最近开展的工作，这些工作使我们了解了这些特征对医学决策算法设计和结果可靠性的影响。
