Big Data Analytics + Virtual Clinical Semantic Network (vCSN): An Approach to Addressing the Increasing Clinical Nuances and Organ Involvement of COVID-19.
ASAIO J
; 67(1): 18-24, 2021 01 01.
Article
in English
| MEDLINE | ID: covidwho-717252
ABSTRACT
The coronavirus disease 2019 (COVID-19) pandemic has revealed deep gaps in our understanding of the clinical nuances of this extremely infectious viral pathogen. In order for public health, care delivery systems, clinicians, and other stakeholders to be better prepared for the next wave of SARS-CoV-2 infections, which, at this point, seems inevitable, we need to better understand this disease-not only from a clinical diagnosis and treatment perspective-but also from a forecasting, planning, and advanced preparedness point of view. To predict the onset and outcomes of a next wave, we first need to understand the pathologic mechanisms and features of COVID-19 from the point of view of the intricacies of clinical presentation, to the nuances of response to therapy. Here, we present a novel approach to model COVID-19, utilizing patient data from related diseases, combining clinical understanding with artificial intelligence modeling. Our process will serve as a methodology for analysis of the data being collected in the ASAIO database and other data sources worldwide.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
Symptom Assessment
/
Semantic Web
/
Data Science
/
Big Data
/
COVID-19
Type of study:
Diagnostic study
/
Prognostic study
Limits:
Humans
Language:
English
Journal:
ASAIO J
Journal subject:
Transplantation
Year:
2021
Document Type:
Article
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