Covid-19 Detection Techniques with X Ray Images Using Machine Learning

COVID-19 has been declared as a pandemic in over 200 countries of the world.COVID-19 is an infectious disease that is primarily caused by severe acute respiratory syndrome corona virus2((SARS-CoV-2). According to the latest figures by the world health organization, the number ofconfirmed cases for the COVID-19 pandemic worldwide is more than 20 million worldwide and thenumber of fatalities reported is over 700,000. It has been found from several studies that medicalimaging coupled with machine learning methods holds great promise in the detection and follow-up ofthe COVID-19 disease due to the enhanced accuracy in results of the experiments performed by theresearchers. Machine Learning (ML)-based solutions can be used to simultaneously analyse multipleinput computed tomography (CT) images of chest and lungs. A large number of papers have beenpublished that show the application of machine learning methods in successful detection of the COVID-19 disease. Such applications demonstrate the suitability of feature prediction, identification of involvedrisks and therefore managing and intercepting the outbreak of such diseases. This paper describes some of the techniques in machine learning that can be used detectionofCOVID-19disease.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-28
DOI
https://doi.org/10.5281/zenodo.17223888
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Covid-19 Detection Techniques with X Ray Images Using Machine Learning

Zenodo (CERN European Organization for Nuclear Research)
COVID-19 diagnosis using AI
article

Covid-19 Detection Techniques with X Ray Images Using Machine Learning

article en

Abstract

COVID-19 has been declared as a pandemic in over 200 countries of the world.COVID-19 is an infectious disease that is primarily caused by severe acute respiratory syndrome corona virus2((SARS-CoV-2). According to the latest figures by the world health organization, the number ofconfirmed cases for the COVID-19 pandemic worldwide is more than 20 million worldwide and thenumber of fatalities reported is over 700,000. It has been found from several studies that medicalimaging coupled with machine learning methods holds great promise in the detection and follow-up ofthe COVID-19 disease due to the enhanced accuracy in results of the experiments performed by theresearchers. Machine Learning (ML)-based solutions can be used to simultaneously analyse multipleinput computed tomography (CT) images of chest and lungs. A large number of papers have beenpublished that show the application of machine learning methods in successful detection of the COVID-19 disease. Such applications demonstrate the suitability of feature prediction, identification of involvedrisks and therefore managing and intercepting the outbreak of such diseases. This paper describes some of the techniques in machine learning that can be used detectionofCOVID-19disease.

Zenodo (CERN European Organization for Nuclear Research)
Good health and well-being
Openalex Percentile: Top 37%
COVID-19 diagnosis using AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.