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Updated: Jun 4, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
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医学成像分析的局部可解释模型-不可知解释方法:一个系统的文献综述

Shahab Ul Hassan1, Said Jadid Abdulkadir2, M Soperi Mohd Zahid1

  • 1Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak, Malaysia; Centre for Intelligent Signal & Imaging Research (CISIR), Universiti Teknologi PETRONAS, Seri Iskandar, 32610, Perak, Malaysia.

Computers in biology and medicine
|December 20, 2024
PubMed
概括

可解释的人工智能 (XAI) 技术,如局部可解释模型不可知解释 (LIME) 对于医疗保健中可靠的人工智能至关重要. 这项研究表明,LIME可以提高机器学习模型的可解释性,从而改善患者的治疗结果.

关键词:
分类 分类 分类 分类.可以解释的可解释性.在 LIME 时代,机器学习 机器学习医疗健康 医疗健康 医疗健康系统的文献审查 系统的文献审查在XAI,XAI就是XAI.

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