Beta blockers may be protective in COVID-19; findings of a study to develop an interpretable machine learning model to assess COVID-19 disease severity in light of clinical findings, medication history, and patient comorbidities-Reference-Cited by-同舟云学术

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Beta blockers may be protective in COVID-19; findings of a study to develop an interpretable machine learning model to assess COVID-19 disease severity in light of clinical findings, medication history, and patient comorbidities

Published:2023 Issue: Volume:42 Page:101341
ISSN:2352-9148
Container-title:Informatics in Medicine Unlocked
language:en
Short-container-title:Informatics in Medicine Unlocked

Author:

Alahmadi Alaa,Alansari Aisha,Alsheikh Nawal,Alshammasi Salam,Alshamery Mona,Al-abdulmohsin Rand,Al Rabia Laila,Al Nass Fatimah,Alghamdi Manar,Almustafa Sarah,Aljamea Zainab,Kurdi Sawsan,Islam Md. Ashraful,Hussein Dania

Publisher

Elsevier BV

Subject

Health Informatics

Reference58 articles.

1. A novel coronavirus outbreak of global health concern;Wang;Lancet (London, England),2020

2. Coronavirus disease 2019: what we know?;He;J Med Virol,2020

3. Obesity, diabetes, hypertension and severe outcomes among inpatients with coronavirus disease 2019: a nationwide study;Bailly;Clin Microbiol Infect,2022

4. Determinants of severity in cancer patients with COVID-19 illness;Robilotti;medRxiv,2020

5. Impact of cardiovascular diseases on severity of COVID-19 patients: a systematic review;Mishra;Ann Acad Med Singapore,2021

Cited by 1 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. Relationships between geo-spatial features and COVID-19 hospitalisations revealed by machine learning models and SHAP values;International Journal of Digital Earth;2024-05-27

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