Predicting the mortality of patients with Covid-19 A machine learning approach: Correspondence

被引:0
|
作者
Ayyoubzadeh, Seyed Mohammad [1 ,2 ]
机构
[1] Univ Tehran Med Sci, Sch Allied Med Sci, Dept Hlth Informat Management, Med Informat, Tehran, Iran
[2] Univ Tehran Med Sci, Sch Allied Med Sci, Hlth Informat Management Dept, 3rd Floor,17 Farredanesh Alley,Ghods St,Enghelab A, Tehran, Iran
关键词
D O I
10.1002/hsr2.1381
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
引用
收藏
页数:1
相关论文
共 50 条
  • [41] The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach
    Mendez-Astudillo, Jorge
    FRONTIERS IN BIG DATA, 2024, 7
  • [42] The machine learning approach for predicting the number of intensive care, intubated patients and death: The COVID-19 pandemic in Turkey
    Cihan, Pinar
    SIGMA JOURNAL OF ENGINEERING AND NATURAL SCIENCES-SIGMA MUHENDISLIK VE FEN BILIMLERI DERGISI, 2022, 40 (01): : 85 - 94
  • [43] A machine learning approach for predicting high risk hospitalized patients with COVID-19 SARS-Cov-2
    Bottrighi, Alessio
    Pennisi, Marzio
    Roveta, Annalisa
    Massarino, Costanza
    Cassinari, Antonella
    Betti, Marta
    Bolgeo, Tatiana
    Bertolotti, Marinella
    Rava, Emanuele
    Maconi, Antonio
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2022, 22 (01)
  • [44] A machine learning approach for predicting high risk hospitalized patients with COVID-19 SARS-Cov-2
    Alessio Bottrighi
    Marzio Pennisi
    Annalisa Roveta
    Costanza Massarino
    Antonella Cassinari
    Marta Betti
    Tatiana Bolgeo
    Marinella Bertolotti
    Emanuele Rava
    Antonio Maconi
    BMC Medical Informatics and Decision Making, 22
  • [45] A machine learning model for predicting deterioration of COVID-19 inpatients
    Noy, Omer
    Coster, Dan
    Metzger, Maya
    Atar, Itai
    Shenhar-Tsarfaty, Shani
    Berliner, Shlomo
    Rahav, Galia
    Rogowski, Ori
    Shamir, Ron
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [46] A machine learning model for predicting deterioration of COVID-19 inpatients
    Omer Noy
    Dan Coster
    Maya Metzger
    Itai Atar
    Shani Shenhar-Tsarfaty
    Shlomo Berliner
    Galia Rahav
    Ori Rogowski
    Ron Shamir
    Scientific Reports, 12
  • [47] Mortality predictors in patients with COVID-19 pneumonia: a machine learning approach using eXtreme Gradient Boosting model
    N. Casillas
    A. M. Torres
    M. Moret
    A. Gómez
    J. M. Rius-Peris
    J. Mateo
    Internal and Emergency Medicine, 2022, 17 : 1929 - 1939
  • [48] A comparison of machine learning algorithms in predicting COVID-19 prognostics
    Ustebay, Serpil
    Sarmis, Abdurrahman
    Kaya, Gulsum Kubra
    Sujan, Mark
    INTERNAL AND EMERGENCY MEDICINE, 2023, 18 (01) : 229 - 239
  • [49] A comparison of machine learning algorithms in predicting COVID-19 prognostics
    Serpil Ustebay
    Abdurrahman Sarmis
    Gulsum Kubra Kaya
    Mark Sujan
    Internal and Emergency Medicine, 2023, 18 : 229 - 239
  • [50] Machine Learning Algorithms for Predicting the Spread of Covid-19 in Indonesia
    Arlis, Syafri
    Defit, Sarjon
    TEM JOURNAL-TECHNOLOGY EDUCATION MANAGEMENT INFORMATICS, 2021, 10 (02): : 970 - 974