A novel combined dynamic ensemble selection model for imbalanced data to detect COVID-19 from complete blood count-Reference-Cited by-同舟云学术

A novel combined dynamic ensemble selection model for imbalanced data to detect COVID-19 from complete blood count

Published:2021-11 Issue: Volume:211 Page:106444
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Wu Jiachao,Shen Jiang,Xu Man,Shao Minglai

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference57 articles.

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4. Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study;Brinati;Journal of Medical Systems,2020

5. Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population;Banerjee;International Immunopharmacology,2020

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