EAPR: explainable and augmented patient representation learning for disease prediction

IF 4.7 3区医学 Q1 MEDICAL INFORMATICS

Health Information Science and Systems Pub Date : 2023-11-14 DOI:10.1007/s13755-023-00256-5

Jiancheng Zhang, Yonghui Xu, Bicui Ye, Yibowen Zhao, Xiaofang Sun, Qi Meng, Yang Zhang, Lizhen Cui

引用次数: 0

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EAPR:用于疾病预测的可解释和增强的患者表征学习

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Health Information Science and Systems MEDICAL INFORMATICS-

CiteScore

11.30

自引率

5.00%

发文量

期刊介绍： Health Information Science and Systems is a multidisciplinary journal that integrates artificial intelligence/computer science/information technology with health science and services, embracing information science research coupled with topics related to the modeling, design, development, integration and management of health information systems, smart health, artificial intelligence in medicine, and computer aided diagnosis, medical expert systems. The scope includes: i.) smart health, artificial Intelligence in medicine, computer aided diagnosis, medical image processing, medical expert systems ii.) medical big data, medical/health/biomedicine information resources such as patient medical records, devices and equipments, software and tools to capture, store, retrieve, process, analyze, optimize the use of information in the health domain, iii.) data management, data mining, and knowledge discovery, all of which play a key role in decision making, management of public health, examination of standards, privacy and security issues, iv.) development of new architectures and applications for health information systems.