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Article
Biology
Wei Wang et al.
Summary: Since 2019, the COVID-19 pandemic has posed a significant threat to the global economy and human health. Deep learning-based computer-aided diagnosis models can effectively alleviate the challenges of diagnosing COVID-19 due to limited healthcare resources. To overcome the time-consuming and unstable nature of traditional hyperparameter tuning methods, we propose a Particle Swarm Optimization-guided Self-Tuning Convolution Neural Network (PSTCNN) that automatically adjusts the model's hyperparameters.
Article
Computer Science, Hardware & Architecture
Xin Zhang et al.
Summary: In this study, a deep learning network-based framework for COVID-19 diagnosis is proposed. By improving AlexNet and introducing three classifiers, three novel models are obtained. Among them, DC-Net-R performs the best on a private dataset and outperforms other existing algorithms.
JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
(2022)
Letter
Biochemistry & Molecular Biology
Alexander H. Thieme et al.
Article
Computer Science, Artificial Intelligence
Amin ul Haq et al.
Summary: This research study provides a comprehensive assessment of deep learning-based diagnostic methodologies for Parkinson's disease recognition. It covers various techniques including data preprocessing, feature extraction, and classification. The study also discusses dataset evaluation, model evaluation metrics, and cross-validation techniques. Additionally, it explores trends and areas for future research in automatic disease recognition, specifically in the detection of Parkinson's disease and its implementation in E-healthcare systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Shahanaz Abdul Gafoor et al.
Summary: The COVID-19 pandemic has had a significant impact globally, and early detection is crucial. This study discusses using Deep Learning methodology to detect coronavirus through image-based modalities, specifically classifying chest X-ray images to determine if a patient is COVID-19 positive or negative.
COGENT ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Shu Liang et al.
Summary: Accurate and timely diagnosis of COVID-19 is crucial for quarantine and medical treatment. Developing a deep learning classification model for detecting COVID-19 through CT images can assist doctors in consultation. The proposed feature complement fusion network (FCF) can extract both local and global features and achieve better feature representation with the attention mechanism in the designed feature complement Transformer (FCT). The model, trained with a supervised and weakly supervised strategy, achieved a high accuracy surpassing the current state-of-art classification models.
APPLIED SOFT COMPUTING
(2022)
Article
Biology
Selene Tomassini et al.
Summary: This article discusses the application of convolutional neural networks in the diagnosis and classification of lung cancer, highlighting their contribution to the accuracy improvement of lung nodule and lung cancer histological type/subtype classification directly from computed tomography data. It points out the strengths and weaknesses of slice-based and scan-based approaches using convolutional neural networks, and emphasizes the challenges and prospective solutions in applying convolutional neural networks for such classification tasks.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Computer Science, Artificial Intelligence
R. Sudharsan et al.
Summary: This paper proposes a novel framework to predict customer churn through the deep learning model S-RNN and analyze the retention process if the customer is identified as churned.
CONNECTION SCIENCE
(2022)
Article
Virology
Mahdi Ouafi et al.
Summary: This study was conducted in the pediatric emergency department of a teaching hospital in Lille, northern France, to investigate viral respiratory infections in children who sought medical attention between February 2021 and January 2022. The results showed a low prevalence of SARS-CoV-2 infection in children, despite the significant increase due to the Delta and Omicron variants. The study also found a high circulation of other respiratory viruses among children.
JOURNAL OF CLINICAL VIROLOGY
(2022)
Article
Engineering, Multidisciplinary
Alok Tiwari et al.
Summary: The study utilized chest X-Rays to identify Covid-19 and other types of pneumonia, and evaluated the model through three case study approaches, showing good performance in terms of accuracy and other parameters.
COGENT ENGINEERING
(2022)
Article
Automation & Control Systems
Qiushi Shi et al.
Summary: This paper proposes a jointly optimized learning strategy for the edRVFL network (JOSedRVFL) for semi-supervised learning tasks. The experimental results demonstrate the superior performance of JOSedRVFL compared to other competition methods in classification tasks.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Gastroenterology & Hepatology
Anja Eberl et al.
Summary: Higher IFX induction concentrations predict short-term endoscopic response in inflammatory bowel diseases (IBD), but do not predict long-term treatment persistence.
EUROPEAN JOURNAL OF GASTROENTEROLOGY & HEPATOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Fatih A. Bogaards et al.
Summary: Lifestyle intervention studies have heterogeneous responses, especially in older adults. This study developed and validated a molecular multivariate biomarker called PLIS that is sensitive to individual effects of lifestyle interventions. The PLIS score demonstrated its ability to track short-term metabolic health gain, with sex-specific differences.
Article
Engineering, Electrical & Electronic
Yudong Zhang et al.
Summary: This study proposed a novel seven layer convolutional neural network based smart diagnosis model for COVID-19 diagnosis in chest CT images. The experimental results show that the proposed model achieves a sensitivity of 94.44 +/- 0.73, a specificity of 93.63 +/- 1.60, and an accuracy of 94.03 +/- 0.80. Data augmentation and stochastic pooling methods are proven to be effective.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Aerospace
James Nash et al.
Summary: This paper presents a novel data-based approach to model the online unsteady and nonlinear response of aircraft by utilizing LiDAR data measured during practical flights. Numerical simulations and neural network training were conducted to validate the proposed method, achieving promising prediction results.
JOURNAL OF AEROSPACE ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Davide Bazzanella et al.
Summary: The nonlinear response of an optical microresonator is utilized in a time multiplexed reservoir computing neural network to solve linear and nonlinear logic operations, showcasing its memory and nonlinearity capabilities.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2022)
Article
Horticulture
Marc-Andre Sparke et al.
Summary: The study showed that exposing tomato plants to intermittent air stimuli can effectively inhibit stem elongation, and the inhibition effect is significantly associated with air velocity. During this process, the dry mass of leaves, stems, and petioles will be reduced to varying degrees.
SCIENTIA HORTICULTURAE
(2022)
Article
Hematology
Robert Marcel T. Huibonhoa et al.
Summary: The study found that physical examination has poor accuracy in detecting CADVT in critically ill children, but combining it with imaging can help understand the clinical significance of asymptomatic CADVT. The method of point-of-care ultrasound and the insertion site of CVC may affect the detection results.
THROMBOSIS RESEARCH
(2022)
Article
Multidisciplinary Sciences
Bijen Khagi et al.
Summary: This paper proposes an activation function based on scaled gamma correction and hyperbolic tangent function, called Scaled Gamma Tanh (SGT) activation. The SGT activation outperforms standard ReLU and tanh activation in MRI classification, as shown by experiments and analysis.
SCIENTIFIC REPORTS
(2022)
Article
Medicine, General & Internal
Theyazn H. H. Aldhyani et al.
Summary: Skin, as the primary protective layer of internal organs, is increasingly prone to various diseases due to pollution and other factors. To address this issue, a lightweight and efficient model for accurate classification of skin lesions is proposed, utilizing dynamic-sized kernels and ReLU/leakyReLU activation functions. The model achieves high overall accuracy and outperforms state-of-the-art heavy models.
Article
Medicine, General & Internal
Noemi Gozzi et al.
Summary: This study utilized pretrained convolutional neural networks to identify abnormalities on chest radiographs, and evaluated their performance using an explainable AI model. The results showed that the best transfer learning model used image embeddings and random forest with simple averaging.
Article
Mathematics, Applied
Liang Chen et al.
Summary: In this note, we estimate the approximation complexity of deep ReLU networks for bandlimited functions in the L∞ sense, and establish a frequency decomposition lemma to support the proof.
Article
Mathematical & Computational Biology
Akansha Singh et al.
Summary: This paper proposes a COVID-19 diagnosis method based on chest X-ray images, using a deep convolutional neural network optimized with the Grasshopper Optimization Algorithm. The results demonstrate high classification accuracy.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Mohamed H. Essai Ali et al.
Summary: This study proposes novel LSTM-based classifiers by developing the internal structure of LSTM neural networks using alternative state activation functions. The simulation results demonstrate that the proposed classifiers outperform the traditional tanh-based LSTM classifiers in terms of classification accuracy.
Article
Computer Science, Information Systems
Ali Olow Jimale et al.
Summary: This study proposes an effective CGAN architecture that synthesizes higher quality samples than existing models for sensor-based activity recognition, particularly using elderly data. The combination of convolutional layers and fully connected networks in the generator's input and discriminator's output contributes to the improved performance of the proposed approach in visual evaluation, similarity measure, and usability evaluation.
Article
Biology
Sertan Serte et al.
Summary: COVID-19, a new type of pneumonia coronavirus, has caused many infections and deaths worldwide. AI techniques can assist radiologists in quickly and accurately detecting COVID-19 infection on CT scans, improving diagnostic efficiency.
COMPUTERS IN BIOLOGY AND MEDICINE
(2021)
Article
Automation & Control Systems
Shanjiang Tang et al.
Summary: Efficient screening of COVID-19 cases is crucial to prevent the rapid spread of the disease, and the EDL-COVID model, combining deep learning and ensemble learning, shows promising results in COVID-19 case detection with a higher accuracy compared to the COVID-Net model.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Geriatrics & Gerontology
Shui-Hua Wang et al.
Summary: The study introduces a novel method for identifying Alzheimer's disease, ADVIAN, utilizing VGG-Inspired network structure and attention mechanisms, combined with 18-way data augmentation, showing superior performance in experiments.
FRONTIERS IN AGING NEUROSCIENCE
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Taro Sugai et al.
Summary: The study aimed to improve the denoising performance of DnCNN by refining the AF and utilizing ParBID for inhomogeneous noise images. Experimental results demonstrated that using Swish increased PSNR and SSIM for all noise levels, while ParBID showed significant improvements in PSNR and SSIM when using three slice images for linear combination. The proposed methods effectively preserved fine structures and image contrast.
MAGNETIC RESONANCE IN MEDICAL SCIENCES
(2021)
Article
Computer Science, Information Systems
Chrisa Tsinaraki et al.
Summary: The study developed a multi-channel approach for monitoring and analyzing COVID-19 related mobile applications, resulting in a dataset with information on 837 apps globally and their availability at different time points. Descriptive findings of app store activities and qualitative information from manual analysis were highlighted in the research.
Article
Biology
Mesut Togacar et al.
COMPUTERS IN BIOLOGY AND MEDICINE
(2020)
Article
Radiology, Nuclear Medicine & Medical Imaging
Qianqian Ni et al.
EUROPEAN RADIOLOGY
(2020)
Article
Infectious Diseases
Kevin Yi-Lwern Yap et al.
INFECTIOUS DISEASES OF POVERTY
(2020)
Article
Health Care Sciences & Services
Hoon Ko et al.
JOURNAL OF MEDICAL INTERNET RESEARCH
(2020)
