Machine Intelligent Techniques for COVID-19 Detection: A Critical Review and Analysis
12th International Conference on Computing Communication and Networking Technologies, ICCCNT 2021
; 2021.
Article
in English
| Scopus | ID: covidwho-1752369
ABSTRACT
Every human being is discussing a highly addressed topic in the current days which is about the COrona VIrus Disease (COVID) in 2019-2020. The outbreak of corona has affected the human race all over the world, the patient count is increasing day by day, and doctors are in a critically need of computer-aided diagnosis with machine learning (ML) algorithms that will discover and diagnose the coronavirus for a large number of patients. Also, it is more complicated to estimate the discharge time and the criticalness of the patient during treatment. Chest computed tomography (CT) scan was the best tool for the corona diagnosis. Also survival analysis methods in ML outperform better in predicting discharge time. In this, we survey on the COVID 19 diagnosis with a chain of CT scan pictures mined from the COVID-19 data set by using ML algorithms like marine predator, simplified suspected infected recovered (SIR), image acquisition, and some more techniques and also survival analysis techniques of ML. The survey clearly explains the models used up to now which are highly defined for the diagnosis of COVID-19 Virus. © 2021 IEEE.
computer-aided diagnosis; COVID-19 Diagnosis; Image Acquisition; Marine Predator; Simplified SIR model; Suspected Infected Recovered (SIR); Bioinformatics; Computer aided analysis; Computer aided instruction; Computerized tomography; Image analysis; Machine learning; Medical computing; Patient treatment; Surveys; Computed tomography scan; Corona virus disease-19 diagnose; Discharge time; Intelligent techniques; Machine learning algorithms; Simplified suspected infected recovered model; Survival analysis; Suspected infected recovered; Virus disease; Computer aided diagnosis
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Reviews
Language:
English
Journal:
12th International Conference on Computing Communication and Networking Technologies, ICCCNT 2021
Year:
2021
Document Type:
Article
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