Development of framework by combining CNN with KNN to detect Alzheimer’s disease using MRI images

Multimedia Tools and Applications, Journal Year: 2022, Volume and Issue: 82(8), P. 12699 - 12717

Published: Sept. 26, 2022

Language: Английский

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An Improved Long Short-Term Memory Algorithm for Cardiovascular Disease Prediction

Diagnostics, Journal Year: 2024, Volume and Issue: 14(3), P. 239 - 239

Published: Jan. 23, 2024

Cardiovascular diseases, prevalent as leading health concerns, demand early diagnosis for effective risk prevention. Despite numerous diagnostic models, challenges persist in network configuration and performance degradation, impacting model accuracy. In response, this paper introduces the Optimally Configured Improved Long Short-Term Memory (OCI-LSTM) a robust solution. Leveraging Salp Swarm Algorithm, irrelevant features are systematically eliminated, Genetic Algorithm is employed to optimize LSTM’s configuration. Validation metrics, including accuracy, sensitivity, specificity, F1 score, affirm model’s efficacy. Comparative analysis with Deep Neural Network Belief establishes OCI-LSTM’s superiority, showcasing notable accuracy increase of 97.11%. These advancements position OCI-LSTM promising accurate efficient cardiovascular diseases. Future research could explore real-world implementation further refinement seamless integration into clinical practice.

Language: Английский

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Fusion of multi-scale bag of deep visual words features of chest X-ray images to detect COVID-19 infection

Scientific Reports, Journal Year: 2021, Volume and Issue: 11(1)

Published: Dec. 13, 2021

Chest X-ray (CXR) images have been one of the important diagnosis tools used in COVID-19 disease diagnosis. Deep learning (DL)-based methods heavily to analyze these images. Compared other DL-based methods, bag deep visual words-based method (BoDVW) proposed recently is shown be a prominent representation CXR for their better discriminability. However, single-scale BoDVW features are insufficient capture detailed semantic information infected regions lungs as resolution such varies real application. In this paper, we propose new multi-scale words (MBoDVW) features, which exploits three different scales 4th pooling layer's output feature map achieved from VGG-16 model. For MBoDVW-based perform Convolution with Max operation over layer using kernels: [Formula: see text], and text]. We evaluate our Support Vector Machine (SVM) classification algorithm on four public datasets (CD1, CD2, CD3, CD4) 5000 Experimental results show that produces stable accuracy (84.37%, 88.88%, 90.29%, 83.65% CD1, CD4, respectively).

Language: Английский

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COL11A1 as an novel biomarker for breast cancer with machine learning and immunohistochemistry validation

Frontiers in Immunology, Journal Year: 2022, Volume and Issue: 13

Published: Oct. 31, 2022

Machine learning (ML) algorithms were used to identify a novel biological target for breast cancer and explored its relationship with the tumor microenvironment (TME) patient prognosis. The edgR package identified hub genes associated overall survival (OS) prognosis, which validated using public datasets. Of 149 up-regulated in tissues, three ML COL11A1 as gene. COL11A1was highly expressed samples poor positively correlated stromal score (r=0.49, p<0.001) ESTIMATE (r=0.29, TME. Furthermore, negatively B cells, CD4 CD8 but cancer-associated fibroblasts. Forty-three related immune-regulation identified, five-gene immune regulation signature was built. Compared clinical factors, this gene an independent risk factor prognosis (HR=2.591, 95%CI 1.831-3.668, p=7.7e-08). A nomogram combining variables, showed better predictive performance (C-index=0.776). model correction prediction curve little bias from ideal curve. is potential therapeutic may be involved infiltration; high expression strongly

Language: Английский

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Enhancement of license plate recognition performance using Xception with Mish activation function

Multimedia Tools and Applications, Journal Year: 2022, Volume and Issue: 82(11), P. 16793 - 16815

Published: Oct. 14, 2022

Language: Английский

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Conv-CapsNet: capsule based network for COVID-19 detection through X-Ray scans

Multimedia Tools and Applications, Journal Year: 2023, Volume and Issue: 82(18), P. 28521 - 28545

Published: Feb. 21, 2023

Language: Английский

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Advances in artificial intelligence for accurate and timely diagnosis of COVID-19: A comprehensive review of medical imaging analysis

Scientific African, Journal Year: 2023, Volume and Issue: 22, P. e01961 - e01961

Published: Nov. 1, 2023

In December 2019, the first case of coronavirus 2019 (COVID-19) appeared in China, quickly leading to a global pandemic. Early and accurate diagnosis is crucial for effective disease management. While reverse transcription polymerase chain reaction (RT-PCR) standard diagnostic test, it may yield false negative misleading results. Artificial intelligence (AI) systems are accelerating transformation medical field, particularly early detection diagnosis. Recent research has combined AI with imaging modalities, such as chest X-ray (CXR) computed tomography (CT), detect virus, aiding doctors making decisions reducing misdiagnosis rates. this article, we conducted systematic review high-quality articles published high-impact journals that examined convolutional neural network (CNN)-based methods detecting COVID-19 from radiographic or CT images discussed associated issues. We synthesized publicly available datasets evaluation measures, including accuracy, sensitivity, specificity, F1 score, each system used automatic using several well-performing CNN architectures. Furthermore, identified key questions future directions field. Our results show use considerable potential improve accuracy reduce Nevertheless, important challenges must be addressed, limited access need rigorous model validation. Additionally, generalization models different populations contexts needs examined. findings underscore directions, exploration deep learning smaller datasets, enhancing performance complex cases, designing practical deployment clinical settings.

Language: Английский

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A hybrid forecasting technique for infection and death from the mpox virus

Digital Health, Journal Year: 2023, Volume and Issue: 9

Published: Jan. 1, 2023

The rising of new cases and death counts from the mpox virus (MPV) is alarming. In order to mitigate impact MPV it essential have information virus's future position using more precise time series stochastic models. this present study, a hybrid forecasting system has been developed for infection world daily cumulative confirmed series.

Language: Английский

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RETRACTED ARTICLE: A review of Deep Learning based methods for Affect Analysis using Physiological Signals

Multimedia Tools and Applications, Journal Year: 2023, Volume and Issue: 82(17), P. 26089 - 26134

Published: Jan. 20, 2023

Language: Английский

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Neurodegenerative diseases detection and grading using gait dynamics

Multimedia Tools and Applications, Journal Year: 2023, Volume and Issue: 82(15), P. 22925 - 22942

Published: Feb. 18, 2023

Language: Английский

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