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Updated: Jan 7, 2026

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
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Published on: December 11, 2019

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可解释的联合学习,通过ECG信任特征进行多类心脏病诊断

Tanjila Alam Sathi1, Rafsan Jany1, Akm Azad2,3

  • 1Department of Computer Science and Engineering, Islamic University of Technology (IUT), Gazipur 1704, Bangladesh.

Diagnostics (Basel, Switzerland)
|December 30, 2025
PubMed
概括

本研究介绍了一种可解释的联合学习框架,用于使用心电图 (ECG) 诊断心脏病. 该模型在分类心律失常和缺血时实现了高精度,同时确保了患者的隐私并提供可解释的结果.

关键词:
在ECG中,信任特征是ECG的信任特征.节律失常 (arrhythmia) 是一种心律失常.身体残疾就是残疾.可解释的人工智能 (XAI)联合学习的联合学习心脏病的分类心脏病的分类缺血缺血症是什么意思 缺血缺血症

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