Predicting COVID-19 Models for Death with Three Different Decision Algorithms: Analysis of 600 Hospitalized Patients
Message:
Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
Introduction
COVID-19 virus has caused the biggest pandemic in a decade. The acute respiratory syndrome caused by this virus can lead to the death of patients. Death is very likely in people with severe forms of lung disease. Early identification of patients with severe disease can be very effective in the prevention of death outcomes with improves triage strategies and timely medical actions. The aim of this study was the prediction of COVID-19 models for death with three different decision algorithms with analysis of hospitalized patients.
Materials and Methods
In this study, in a retrospective analysis of 600 COVID-19 patients, we apply three decision tree algorithms including the C5.0, CRT, and CHAID using all related factors to the disease including demographic data, history of exposure, clinical signs, and symptoms, laboratory results, chest X-ray or computed tomography (CT) scans, underlying illness, treatment steps, and outcomes of each patient to build several models predicting the death of Covid-19 infection.
Results
The accuracy of the models was above 90%. Overall, in our retrospective analysis, age, hypertension, lung disease, O2Sat, diabetes, and body temperature, respectively are the most important factors that can affect the mortality rate of COVID-19 patients. Among them, age, and hypertension are common in our applied three models.
Conclusions
The design of such models and apply in hospitals can help to improve disease management and decrease the mortality rate spatially in about recent pandemic.
Language:
English
Published:
Journal of Applied Biotechnology Reports, Volume:10 Issue: 2, Spring 2023
Pages:
1018 to 1024
magiran.com/p2595090  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 990,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 50 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!