Consistent comparison of symptom-based methods for COVID-19 infection detection-Reference-Cited by-同舟云学术

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Consistent comparison of symptom-based methods for COVID-19 infection detection

Published:2023-09 Issue: Volume:177 Page:105133
ISSN:1386-5056
Container-title:International Journal of Medical Informatics
language:en
Short-container-title:International Journal of Medical Informatics

Author:

Rufino Jesús,Ramírez Juan Marcos^ORCID,Aguilar Jose,Baquero Carlos,Champati Jaya,Frey Davide,Lillo Rosa Elvira,Fernández-Anta Antonio

Publisher

Elsevier BV

Subject

Health Informatics

Reference30 articles.

1. Virological assessment of hospitalized patients with COVID-2019;Wölfel;Nature,2020

2. Applications of digital technology in COVID-19 pandemic planning and response;Whitelaw;Lancet Digit. Health,2020

3. Diagnostic testing for severe acute respiratory syndrome–related coronavirus 2: a narrative review;Cheng;Ann. Intern. Med.,2020

4. An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China;Tian;Science,2020

5. Machine learning-based prediction of COVID-19 diagnosis based on symptoms;Zoabi;npj Digit. Med.,2021

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. COVID-19 seroprevalence estimation and forecasting in the USA from ensemble machine learning models using a stacking strategy;Expert Systems with Applications;2024-12

2. A Stacking Ensemble Machine Learning Strategy for COVID-19 Seroprevalence Estimations in the USA Based on Genetic Programming;2024 IEEE Congress on Evolutionary Computation (CEC);2024-06-30

3. Performance and explainability of feature selection-boosted tree-based classifiers for COVID-19 detection;Heliyon;2024-01

4. Detection and risk assessment of COVID-19 through machine learning;International Journal of ADVANCED AND APPLIED SCIENCES;2024-01

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