Optimized network based natural language processing approach to reveal disease comorbidities in COVID-19.

ABSTRACT: A novel virus emerged from Wuhan, China, at the end of 2019 and quickly evolved into a pandemic, significantly impacting various industries, especially healthcare. One critical lesson from COVID-19 is the importance of understanding and predicting underlying comorbidities to better prioritize care and pharmacological therapies. Factors like age, race, and comorbidity history are crucial in determining disease mortality. While clinical data from hospitals and cohorts have led to the identification of these comorbidities, traditional approaches often lack a mechanistic understanding of the connections between them. In response, we utilized a deep learning approach to integrate COVID-19 data with data from other diseases, aiming to detect comorbidities with mechanistic insights. Our modified

SUBMITTER: Duman ET 

PROVIDER: S-EPMC10822845 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature