Metabolomics in the prediction of prodromal stages of carotid artery disease using a hybrid ML algorithm-Reference-Cited by-同舟云学术

Metabolomics in the prediction of prodromal stages of carotid artery disease using a hybrid ML algorithm

Published:2022-09-27 Issue: Volume: Page:
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Container-title:2022 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)
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Author:

Pezoulas Vasileios¹,Mishra Pashupati P.²,Raitakari Olli T.³,Kahonen Mika⁴,Lehtimaki Terho²,Fotiadis Dimitrios I.⁵,Sakellarios Antonis I.⁶

Affiliation:

1. Unit of Medical Technology and Intelligent Information Systems,Dept. of Materials Science and Engineering,Ioannina,Greece

2. Finnish cardiovascular research center,Faculty of medicine and health technology,Dept. of clinical chemistry,Tambere

3. Research centre of applied and preventive cardiovascular medicine, University of Turku,Turku,Finland

4. Finnish cardiovascular research center,Faculty of medicine and health technology,Tampere

5. Biomedical Resarch Institute, FORTH-IMBB,Unit of Medical Technology and Intelligent Information Systems,Dept. of Materials Science and Engineering,Ioannina,Greece,GR 45110

6. Biomedical Resarch Institute, FORTH-IMBB,Unit of Medical Technology and Intelligent Information Systems,Dept. of Materials Science and Engineering,Ioannina,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9926747/9926739/09926774.pdf?arnumber=9926774

Reference19 articles.

1. The Comparison of LightGBM and XGBoost Coupling Factor Analysis and Prediagnosis of Acute Liver Failure

2. A Novel PCA-Firefly Based XGBoost Classification Model for Intrusion Detection in Networks Using GPU

3. XGBoost

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