Authors :
Upendra Chauhan; Ramkrishna Singh; Ramandeep Kaur; Shubham Singh; Tanisha Kumari; Ankur Chauhan
Volume/Issue :
Volume 8 - 2023, Issue 11 - November
Google Scholar :
https://tinyurl.com/yetd93hc
Scribd :
https://tinyurl.com/694rcx4x
DOI :
https://doi.org/10.5281/zenodo.10213496
Abstract :
Developing an advanced COVID-19 screening
scheme using Azure’s heterogeneous datasets coupled
with ECDC data. Combining comprehensive datasets,
including medical records, radiological imaging scan,
clinical details, and epidemiological information from
ECDC will produce a refined and accurate model for
diagnosing COVID-19 and integrating the capabilities of
data lakes and data warehouses. Azure’s dataset
integration incorporates information like X- rays, CT
scans, patient demographics, clinical symptoms,while
ECDC data encompasses broad epidemiological,
transmission rates, and geographical spread. The final
aim is to present healthcare practitioners with a
diagnostic aid for rapid and accurate differentiation of a
COVID-19 positive and non- COVID-19 patient thus
facilitating immediate patient management and framing
response measures to be put into place during
pandemics. Using the extensive epidemiological data
repository generated by the European Center for Disease
Prevention and Control (ECDC) coupled with its Azure
services, including Azure Data Lake Storage, Azure
Databricks, and Power BI, the development efforts
would be focused on creating an adaptable approach for
prompt detection of new COVID-19 cases, enabling
healthcare institutions.
Keywords :
COVID-19, Healthcare Management, Azure Data Factory, Azure Data Storage.
Developing an advanced COVID-19 screening
scheme using Azure’s heterogeneous datasets coupled
with ECDC data. Combining comprehensive datasets,
including medical records, radiological imaging scan,
clinical details, and epidemiological information from
ECDC will produce a refined and accurate model for
diagnosing COVID-19 and integrating the capabilities of
data lakes and data warehouses. Azure’s dataset
integration incorporates information like X- rays, CT
scans, patient demographics, clinical symptoms,while
ECDC data encompasses broad epidemiological,
transmission rates, and geographical spread. The final
aim is to present healthcare practitioners with a
diagnostic aid for rapid and accurate differentiation of a
COVID-19 positive and non- COVID-19 patient thus
facilitating immediate patient management and framing
response measures to be put into place during
pandemics. Using the extensive epidemiological data
repository generated by the European Center for Disease
Prevention and Control (ECDC) coupled with its Azure
services, including Azure Data Lake Storage, Azure
Databricks, and Power BI, the development efforts
would be focused on creating an adaptable approach for
prompt detection of new COVID-19 cases, enabling
healthcare institutions.
Keywords :
COVID-19, Healthcare Management, Azure Data Factory, Azure Data Storage.
