Evidence map›Paper›PMID 38624787›Full record

ArticleAnnals of data science2022

Data Analysis of COVID-19 Hospital Records Using Contextual Patient Classification System.

Vrushabh Gada, Madhura Shegaonkar, Madhura Inamdar, Sharath Dinesh, Darshan Sapariya, Vedant Konde, Mahesh Warang, Ninad Mehendale

Abstract read
In one paragraph

Article in Annals of data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Vrushabh GadaK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Madhura ShegaonkarK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Madhura InamdarK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Sharath DineshK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Darshan SapariyaK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Vedant KondeK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Mahesh WarangK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.
Ninad MehendaleK. J. Somaiya College of Engineering, Mumbai, Maharashtra 400077 India.ORCID 0000-0003-3037-5076

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Humanity today is suffering from one of the most dangerous pandemics in history, the Coronavirus Disease of 2019 (COVID-19). Although today there is immense advancement in the medical field with the latest technology, the COVID-19 pandemic has affected us severely. The virus is spreading rapidly, resulting in an escalation in the number of patients admitted. We propose a contextual patient classification system for better analysis of the data from the discharge summary available from the research hospital. The classification was done using the Knuth-Morris-Pratt algorithm. We have also analyzed the data of COVID-19 and non-COVID-19 patients. During the analysis, studies on the medicines, medical services and tests, pulse count, body temperature, and the overall effect of age and gender was done. The death versus survival ratio for the COVID-19 positive patients has also been studied. The classification accuracy of the contextual patient classification system achieved was 97.4%. The combination of data analysis and contextual patient classification will be helpful to all the sectors to be better prepared for any future waves of the COVID-19 pandemic.

Indexed as

Contextual searchData analysisPatient classification system

Identifiers

PMID38624787
PMCPMC8939496

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.