Machine learning applications for COVID-19 outbreak management

Neural Computing and Applications, Journal Year: 2022, Volume and Issue: 34(18), P. 15313 - 15348

Published: June 10, 2022

Language: Английский

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Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations

Computers in Biology and Medicine, Journal Year: 2023, Volume and Issue: 163, P. 107191 - 107191

Published: June 20, 2023

Language: Английский

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Unified deep learning models for enhanced lung cancer prediction with ResNet-50–101 and EfficientNet-B3 using DICOM images

BMC Medical Imaging, Journal Year: 2024, Volume and Issue: 24(1)

Published: March 18, 2024

Abstract Significant advancements in machine learning algorithms have the potential to aid early detection and prevention of cancer, a devastating disease. However, traditional research methods face obstacles, amount cancer-related information is rapidly expanding. The authors developed helpful support system using three distinct deep-learning models, ResNet-50, EfficientNet-B3, ResNet-101, along with transfer learning, predict lung thereby contributing health reducing mortality rate associated this condition. This offer aims address issue effectively. Using dataset 1,000 DICOM cancer images from LIDC-IDRI repository, each image classified into four different categories. Although deep still making progress its ability analyze understand data, marks significant step forward fight against promoting better outcomes potentially lowering rate. Fusion Model, like all other achieved 100% precision classifying Squamous Cells. Model ResNet-50 90%, closely followed by EfficientNet-B3 ResNet-101 slightly lower precision. To prevent overfitting improve data collection planning, implemented extension strategy. relationship between acquiring knowledge reaching specific scores was also connected advancing addressing imprecise accuracy, ultimately reduction cancer.

Language: Английский

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Deep learning on medical image analysis

CAAI Transactions on Intelligence Technology, Journal Year: 2024, Volume and Issue: unknown

Published: June 24, 2024

Abstract Medical image analysis plays an irreplaceable role in diagnosing, treating, and monitoring various diseases. Convolutional neural networks (CNNs) have become popular as they can extract intricate features patterns from extensive datasets. The paper covers the structure of CNN its advances explores different types transfer learning strategies well classic pre‐trained models. also discusses how has been applied to areas within medical analysis. This comprehensive overview aims assist researchers, clinicians, policymakers by providing detailed insights, helping them make informed decisions about future research policy initiatives improve patient outcomes.

Language: Английский

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Global research trends of immunosenescence and immunotherapy: A bibliometric study

Human Vaccines & Immunotherapeutics, Journal Year: 2025, Volume and Issue: 21(1)

Published: Feb. 24, 2025

Immunosenescence refers to the gradual decline in immune system function with age, increasing susceptibility infections and cancer elderly. The advent of novel immunotherapies has revolutionized field treatment. However, majority patients exhibit poor re-sponses immunotherapy, immunosenescence likely playing a significant role. In recent years, progress been made understanding interplay between immunotherapy. Our research aims explore prospects development trends immunotherapy using bibliometric analysis. Relevant articles were collected from Web Science Core Collection (WoSCC) (retrieved on July 20, 2024). Primary characteristics analyzed R package "Biblio-metrix," keyword co-occurrence analysis visualization conducted VOSviewer. A total 213 English-language original review spanning 35 years re-trieved for There was surge publications this starting 2017. United States China contributed most articles. Frontiers Immunology productive journal, while University California System highest contributing institution. Besse Benjamin France emerged as influential researcher field. Popular keywords included "nivolumab," "T cells," "dendritic "regulatory T cells." "immunosenescence-associated secretory phenotype" become new hotspot, checkpoint inhibitors remaining central theme domain. is entering phase rapid will continue hold value future research.

Language: Английский

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A review on lung disease recognition by acoustic signal analysis with deep learning networks

Journal Of Big Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: June 12, 2023

Abstract Recently, assistive explanations for difficulties in the health check area have been made viable thanks considerable portion to technologies like deep learning and machine learning. Using auditory analysis medical imaging, they also increase predictive accuracy prompt early disease detection. Medical professionals are thankful such technological support since it helps them manage further patients because of shortage skilled human resources. In addition serious illnesses lung cancer respiratory diseases, plurality breathing is gradually rising endangering society. Because prediction immediate treatment crucial disorders, chest X-rays sound audio proving be quite helpful together. Compared related review studies on classification/detection using algorithms, only two based signal diagnosis conducted 2011 2018. This work provides a recognition with acoustic networks. We anticipate that physicians researchers working sound-signal-based will find this material beneficial.

Language: Английский

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YOLOv5s-CBAM-DMLHead: A lightweight identification algorithm for weedy rice (Oryza sativa f. spontanea) based on improved YOLOv5

Crop Protection, Journal Year: 2023, Volume and Issue: 172, P. 106342 - 106342

Published: July 7, 2023

Language: Английский

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Improved Latin hypercube sampling initialization-based whale optimization algorithm for COVID-19 X-ray multi-threshold image segmentation

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: June 9, 2024

Image segmentation techniques play a vital role in aiding COVID-19 diagnosis. Multi-threshold image methods are favored for their computational simplicity and operational efficiency. Existing threshold selection multi-threshold segmentation, such as Kapur based on exhaustive enumeration, often hamper efficiency accuracy. The whale optimization algorithm (WOA) has shown promise addressing this challenge, but issues persist, including poor stability, low efficiency, accuracy segmentation. To tackle these issues, we introduce Latin hypercube sampling initialization-based multi-strategy enhanced WOA (CAGWOA). It incorporates COS initialization strategy (COSI), an adaptive global search approach (GS), all-dimensional neighborhood mechanism (ADN). COSI leverages probability density functions created from sampling, ensuring even solution space coverage to improve the stability of model. GS widens exploration scope combat stagnation during iterations ADN refines convergence around optimal individuals CAGWOA's performance is validated through experiments various benchmark function test sets. Furthermore, apply CAGWOA alongside similar model comparative lung X-ray images infected patients. results demonstrate superiority, better detail preservation, clear boundaries, adaptability across different levels.

Language: Английский

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Mapping the knowledge landscape of the PET/MR domain: a multidimensional bibliometric analysis

European Journal of Nuclear Medicine and Molecular Imaging, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 4, 2025

Language: Английский

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Quantum generative adversarial network for image generation

The Visual Computer, Journal Year: 2025, Volume and Issue: unknown

Published: May 13, 2025

Language: Английский

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