Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis

Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis

Abstract Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal clinical records. The motivation stems from the need for timely medical resource allocation, improved treatment decisions during pandemics, and...

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Main Authors: Seung Hwan Bae, Donghee Kim, Jaeyeon Jang, A-Sol Kim, Soyoon Hwang, Eunkyung Nam, Sohyun Bae, Ji Yeon Lee, Ji Sun Kim, Sang Cheol Kim, Hye-Yeong Jo, Kwangsoo Kim, Inuk Jung, Ki Tae Kwon
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Severity
Progression
Time course
Deep learning
Single-cell
Online Access:https://doi.org/10.1038/s41598-025-07793-x
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https://doi.org/10.1038/s41598-025-07793-x

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