SUPERVISED MACHINE LEARNING PREDICTS MORTALITY IN COVID-19 PATIENTS USING ELECTRONIC HEALTH RECORDS

被引:0
|
作者
Marinaro, X. [1 ]
Meng, Z. [1 ]
Zhang, X. [1 ]
Lodaya, K. [1 ]
Hayashida, D. K. [1 ]
Munson, S. [1 ]
D'Souza, F. [1 ]
机构
[1] Boston Strateg Partners Inc, Boston, MA USA
关键词
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
ML2
引用
收藏
页码:S11 / S11
页数:1
相关论文
共 50 条
  • [1] Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach
    Vaid, Akhil
    Jaladanki, Suraj K.
    Xu, Jie
    Teng, Shelly
    Kumar, Arvind
    Lee, Samuel
    Somani, Sulaiman
    Paranjpe, Ishan
    De Freitas, Jessica K.
    Wanyan, Tingyi
    Johnson, Kipp W.
    Bicak, Mesude
    Klang, Eyal
    Kwon, Young Joon
    Costa, Anthony
    Zhao, Shan
    Miotto, Riccardo
    Charney, Alexander W.
    Boettinger, Erwin
    Fayad, Zahi A.
    Nadkarni, Girish N.
    Wang, Fei
    Glicksberg, Benjamin S.
    [J]. JMIR MEDICAL INFORMATICS, 2021, 9 (01)
  • [2] Unsupervised Machine Learning for the Discovery of Latent Clusters in COVID-19 Patients Using Electronic Health Records
    Cui, Wanting
    Robins, Daniel
    Finkelstein, Joseph
    [J]. IMPORTANCE OF HEALTH INFORMATICS IN PUBLIC HEALTH DURING A PANDEMIC, 2020, 272 : 1 - 4
  • [3] Predict Pregnancy Outcomes in the COVID-19 Pandemic Using Electronic Health Records and Machine Learning Approach
    Lyu, Tianchu
    Liang, Chen
    [J]. 2022 IEEE 10TH INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI 2022), 2022, : 483 - 483
  • [4] Using Electronic Health Records to Accurately Predict COVID-19 Health Outcomes through a Novel Machine Learning Pipeline
    Feng, Alice
    [J]. 12TH ACM CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY, AND HEALTH INFORMATICS (ACM-BCB 2021), 2021,
  • [5] Using Electronic Health Records for Predicting Hospitalization of COVID-19 Patients in Massachusetts
    Dashti, Hesam
    Roche, Elise C.
    Bates, David W.
    Cook, Nancy R.
    Mora, Samia
    Demler, Olga
    [J]. CIRCULATION, 2020, 142
  • [6] Machine Learning for Mortality Analysis in Patients with COVID-19
    Sanchez-Montanes, Manuel
    Rodriguez-Belenguer, Pablo
    Serrano-Lopez, Antonio J.
    Soria-Olivas, Emilio
    Alakhdar-Mohmara, Yasser
    [J]. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2020, 17 (22) : 1 - 20
  • [7] Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records
    Zapata, Ruben D.
    Huang, Shu
    Morris, Earl
    Wang, Chang
    Harle, Christopher
    Magoc, Tanja
    Mardini, Mamoun
    Loftus, Tyler
    Modave, Francois
    [J]. PLOS ONE, 2023, 18 (10):
  • [8] Real-time prediction of COVID-19 related mortality using electronic health records
    Patrick Schwab
    Arash Mehrjou
    Sonali Parbhoo
    Leo Anthony Celi
    Jürgen Hetzel
    Markus Hofer
    Bernhard Schölkopf
    Stefan Bauer
    [J]. Nature Communications, 12
  • [9] Real-time prediction of COVID-19 related mortality using electronic health records
    Schwab, Patrick
    Mehrjou, Arash
    Parbhoo, Sonali
    Celi, Leo Anthony
    Hetzel, Jurgen
    Hofer, Markus
    Scholkopf, Bernhard
    Bauer, Stefan
    [J]. NATURE COMMUNICATIONS, 2021, 12 (01)
  • [10] Stratification of the Mortality Risk of COVID-19 Patients by using Machine Learning Algorithms
    Reuther, Janina
    Fomenko, Vlad
    Guelow, Karsten
    Reuther, Stefan
    Spreiter, Lucas
    Schmid, Stephan
    Mueller-Schilling, Martina
    [J]. INTERNIST, 2021, 62 (SUPPL 2): : 197 - 197