Detection of COVID-19 Based on Chest X-rays Using Deep Learning

Walaa Gouda, Maram Almurafeh, Mamoona Humayun, Noor Zaman Jhanjhi

Healthcare 2022 article cited by 132

Source Open-access PDF More in Medicine & Health

importance 8/10 partially solved COVID-19 diagnosis using AI infectious disease radiology stage: research

Problem

Fast, reliable early detection of COVID-19 from chest X-ray images to support diagnosis and isolation decisions.

Why it matters

Early COVID-19 diagnosis was crucial to slowing pandemic spread and guiding patient care.

What the AI did

An ensemble of multiple runs of a modified pretrained ResNet-50 classified chest X-ray images as COVID-19 or not, after preprocessing (augmentation, enhancement, normalization, resizing).

Results

not stated in source

Impact

The abstract claims dominance over VGG and DenseNet on two public benchmark datasets, but no concrete numbers are given.

Record

Venue	Healthcare
Published	2022
Work type	article
Authors	Walaa Gouda, Maram Almurafeh, Mamoona Humayun, Noor Zaman Jhanjhi
Citations	132 (OpenAlex, at import time)
References	47
Model or method	Modified ResNet-50 ensemble
Organization	not stated in source
Primary source	https://doi.org/10.3390/healthcare10020343
Open access	gold
Keywords	COVID-19, chest X-ray, deep learning, ResNet-50, ensemble, image classification

Importance rating

8 / 10

major — millions of lives, an industry or a field

Abstract states COVID-19 is rapidly spreading worldwide and early diagnosis/isolation is crucial to slowing spread, framing a pandemic-scale problem; solution evaluated only on public benchmark datasets.

Basis: stated. The source itself states the scale. Stated scale: not stated in source. Method and limits.

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