An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence

Author:

Wang Shaobo1ORCID,Du Xinhui2ORCID,Liu Guangliang2ORCID,Xing Hang2ORCID,Jiao Zengtao2ORCID,Yan Jun2ORCID,Liu Youjun1ORCID,Lv Haichen3ORCID,Xia Yunlong3ORCID

Affiliation:

1. Beijing University of Technology, Beijing, China

2. Yidu Cloud, Beijing Technology Company Ltd., Beijing, China

3. Department of Cardiology, First Affiliated Hospital of Dalian Medical University, Dalian, China

Funder

National Natural Science Foundation of China

Prof. Lv, in part by Dalian Youth Science and Technology Star Support Program

Prof. Lv, in part by the National Natural Science Foundation of China

Natural Science Foundation of Liaoning Province

Service platform for active monitoring

Early Warning and Prevention and Control of Serious Infectious Diseases

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

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3. Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study

4. Lymphocyte count and prognosis in patients with heart failure

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