Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review

PeerJ Computer Science, Journal Year: 2024, Volume and Issue: 10, P. e2517 - e2517

Published: Dec. 24, 2024

The global spread of SARS-CoV-2 has prompted a crucial need for accurate medical diagnosis, particularly in the respiratory system. Current diagnostic methods heavily rely on imaging techniques like CT scans and X-rays, but identifying these images proves to be challenging time-consuming. In this context, artificial intelligence (AI) models, specifically deep learning (DL) networks, emerge as promising solution image analysis. This article provides meticulous comprehensive review imaging-based diagnosis using up May 2024. starts with an overview covering basic steps learning-based data sources, pre-processing methods, taxonomy techniques, findings, research gaps performance evaluation. We also focus addressing current privacy issues, limitations, challenges realm diagnosis. According taxonomy, each model is discussed, encompassing its core functionality critical assessment suitability detection. A comparative analysis included by summarizing all relevant studies provide overall visualization. Considering best deep-learning detection, conducts experiment twelve contemporary techniques. experimental result shows that MobileNetV3 outperforms other models accuracy 98.11%. Finally, elaborates explores potential future directions methodological recommendations advancement.

Language: Английский

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Machine Learning-Driven Exploration and Stages Classification of Liver Cirrhosis: A Comprehensive Approach

Published: Aug. 7, 2024

Language: Английский

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Hybrid Model Combining BPNN and SVM-RBF Classifiers for Diagnosis

International Journal of Scientific Methods in Engineering and Management, Journal Year: 2023, Volume and Issue: 01(08), P. 09 - 17

Published: Jan. 1, 2023

The global prevalence of cancer as a leading cause death in women is undeniable.If we can get better at finding and treating cancer, it will be huge boon to people's health longevity.As result, having accurate prediction capabilities high grade very necessary order maintain up-to-date treatment survival requirements for patients.The detection breast an early stage has been major focus study recent years, techniques based on machine learning have shown successful methodology.In this investigation, used total five distinct approaches.It not development empirical investigations therapy include the use other kinds soft computing.The wide range cancers well their all over world are addressed.It cannot overstated how important able recognise anomalies distinguish between benign malignant cancer.Diagnostic models created that both Levenberg-Marquardt (LM) Sparse Representation (SR) algorithms.A great performance terms accuracy mean square error was achieved result

Language: Английский

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Enhancing Image Quality through Convolutional Neural Network-based Image Denoising

Published: March 29, 2023

Enhancing Image Quality through Convolutional NeuralNetwork-based Denoising

Language: Английский

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Machine learning algorithms are used to build models of the wireless environment

Published: March 29, 2023

Machine learning algorithms are used to build models of the wireless environmen

Language: Английский

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Enhancing Image Quality through Convolutional Neural Networkbased Image Denoising

Published: March 29, 2023

Enhancing Image Quality through Convolutional Neural Networkbased Denoising

Language: Английский

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Convolutional Neural Network-based Image Denoising for High-Quality Image Reconstruction

Published: March 29, 2023

Convolutional Neural Network-based Image Denoising forHigh-Quality Reconstruction

Language: Английский

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Deep Learning-based Image Denoising for Enhanced Image Quality using Convolutional Neural Networks

Published: March 29, 2023

Deep Learning-based Image Denoising for Enhanced Qualityusing Convolutional Neural Networks

Language: Английский

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Enhancing COVID-19 Diagnosis with CXGNet: A Deep CNN and Optimizer for Tri-Phase Chest X-ray Images

Published: March 29, 2023

Enhancing COVID-19 Diagnosis with CXGNet: A Deep CNN and Optimizerfor Tri-Phase Chest X-ray Images

Language: Английский

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Enhancing Image Quality through Convolutional Neural Network-based Image Denoising

Published: March 29, 2023

Enhancing Image Quality through Convolutional NeuralNetwork-based Denoising

Language: Английский

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