This paper is in the following e-collection/theme issue:

Theme Issue: Medical Informatics and COVID-19 (115) Artificial Intelligence (1603) Clinical Information and Decision Making (1548) JMIR Theme Issue: COVID-19 Special Issue (2478) Decision Support for Health Professionals (1288) Imaging Informatics (215) Machine Learning (1627) Infectious Diseases (non-STD/STI) (1633) Outbreak and Pandemic Preparedness and Management (1771)

Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24973, first published .
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Authors of this article:

Thao Thi Ho1 Author Orcid Image ;   Jongmin Park2 Author Orcid Image ;   Taewoo Kim1 Author Orcid Image ;   Byunggeon Park2 Author Orcid Image ;   Jaehee Lee3 Author Orcid Image ;   Jin Young Kim4 Author Orcid Image ;   Ki Beom Kim5 Author Orcid Image ;   Sooyoung Choi6 Author Orcid Image ;   Young Hwan Kim7 Author Orcid Image ;   Jae-Kwang Lim2 Author Orcid Image ;   Sanghun Choi1 Author Orcid Image
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New JMIR MedInform: Deep Learning Models for Predicting Severe Progression in #covid19-Infected #patients: Retrospe… https://t.co/jvAKVb8U8s

3:01 PM · Jan 28, 2021

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Phil Phil @phil_w888

2,352/ Korea (current tobacco smoking age 15+ was 22.6% in 2017) Of 297 Covid-19 patients who had a chest CT scan… https://t.co/oZWW24lHDR

1:44 AM · Feb 10, 2021

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