Review
Physics, Multidisciplinary
Rodrigo Capobianco Guido
Summary: Wavelet-based analyses have made remarkable achievements in physics and related sciences. However, many people still misunderstand the fundamentals of wavelets. This article provides clear explanations of different types of wavelet transforms and their applications, helping readers to effectively utilize wavelets in their research.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Review
Neurosciences
Francis A. M. Manno, Raul Rodriguez-Cruces, Rachit Kumar, J. Tilak Ratnanather, Condon Lau
Summary: Hearing loss, a heterogeneous disorder, is found to impact grey and white matter in nearly every brain region according to MRI studies. Congenital loss decreases grey matter in frontal lobe most, while acquired loss shows significant decreases in both frontal and insula grey matter. Different impacts on hemispheres are observed between congenital and acquired hearing loss.
Review
Medicine, Research & Experimental
Shadi Ahmadmehrabi, Jason Brant, Douglas J. Epstein, Michael J. Ruckenstein, Daniel J. Rader
Summary: The traditional focus in literature and clinical practice on adult-onset hearing loss has been on environmental risk factors, but recent studies have shown increasing evidence of gene-environment interactions playing a role in adult cases of HL. Susceptibility loci for age-related HL have been identified, and genes related to postlingual nonsyndromic HL continue to be discovered through individual reports and genome-wide association studies.
Article
Medicine, General & Internal
Erum Naz, Ghulam Saqulain, Nazia Mumtaz, Muhammad Naveed Babur
Summary: This study analyzed the prevalence and characteristics of sudden sensorineural hearing loss, revealing that it is more common in males and in the age group of 15-25 years. It is mainly characterized by severe to profound degree of hearing loss, downward sloping audiogram, and is not associated with vertigo or tinnitus.
PAKISTAN JOURNAL OF MEDICAL SCIENCES
(2021)
Article
Medicine, General & Internal
Hwa-Sung Rim, Myung-Gu Kim, Dong-Choon Park, Sung-Soo Kim, Dae-Woong Kang, Sang-Hoon Kim, Seung-Geun Yeo
Summary: The study revealed a close relationship between metabolic syndrome and hearing loss, with the number of components of metabolic syndrome positively correlated with the rate of sensorineural hearing loss.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Multidisciplinary Sciences
Nobuyoshi Tsuzuki, Koichiro Wasano, Naoki Oishi, Ko Hentona, Marie Shimanuki, Takanori Nishiyama, Yoshihiko Hiraga, Seiichi Shinden, Kaoru Ogawa
Summary: The study aimed to investigate the association between idiopathic sudden sensorineural hearing loss (idiopathic SSNHL) and stroke risk in patients, suggesting that circulatory disorders may be a primary cause of severe idiopathic SSNHL in individuals at high risk of stroke. The results indirectly supported the hypothesis by showing a significantly lower rate of vestibular schwannoma (VS) in high-stroke-risk patients with severe hearing loss compared to low-stroke-risk individuals.
SCIENTIFIC REPORTS
(2021)
Article
Environmental Sciences
Chia-Huang Chang, Chun-Ting Lu, Tai-Ling Chen, Wen-Tzu Huang, Pao-Chuan Torng, Chen-Wei Chang, Yu-Chun Chen, Yu-Lin Yu, Yung-Ning Chuang
Summary: This study found an association between exposure to BPA and PBs and sensorineural hearing loss in children through hearing tests, confirming the impact of BPA and PBs on hearing loss in children. Further research needs to be expanded to include cohort designs and nationwide studies to identify causality.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Dermatology
Sheng-Hsiang Ma, Min-De Ang, Yun-Ting Chang, Ying-Xiu Dai
Summary: The study revealed a significant association between vitiligo and sensorineural hearing loss, supporting the importance of audiologic assessment for early recognition and management of hearing loss in patients with vitiligo.
JOURNAL OF THE AMERICAN ACADEMY OF DERMATOLOGY
(2021)
Article
Computer Science, Artificial Intelligence
Yueyue Yao, Jianghong Ma, Yunming Ye
Summary: In this paper, a regularized autoencoder model is proposed to capture specific features of normal sequences for anomaly detection. By performing statistical analysis on input sequences, spectral unique patterns are captured and a Weight Controller is designed to calculate sample-adaptive regularization weights, leading to improved effectiveness and superiority compared with state-of-the-art algorithms.
PATTERN RECOGNITION
(2023)
Review
Engineering, Biomedical
Mustafa Nazir Okur, Hamid R. Djalilian
Summary: Mitochondria are crucial organelles involved in various cellular functions and their dysfunction is implicated in many diseases, especially neurodegenerative disorders. Targeting mitochondrial dysfunction is important in the progression of sensorineural hearing loss.
ANNALS OF BIOMEDICAL ENGINEERING
(2022)
Article
Public, Environmental & Occupational Health
Pei-Xun Zhong, I-Hsun Li, Jui-Hu Shih, Chin-Bin Yeh, Kuan-Wei Chiang, Li-Ting Kao
Summary: The use of antidepressants, regardless of class, has been found to increase the risk of sudden sensorineural hearing loss. Patients taking a higher number of classes of antidepressants are at a higher risk of developing SSNHL compared to those taking a lower number of classes.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Biochemistry & Molecular Biology
Reyhaneh Abgoon, Printha Wijesinghe, Cathie Garnis, Desmond A. Nunez
Summary: Sudden sensorineural hearing loss (SSNHL) is an acquired idiopathic hearing loss. This study aimed to determine if the differential expression of miRNAs persists in SSNHL patients within 1 month of hearing loss onset compared to patients 3-12 months after hearing loss onset. The study found no significant difference in miRNA expression levels, hearing recovery status, and initial and final affected ear PTA audiometric thresholds between the two groups.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Genetics & Heredity
Min Liu, Yue Liang, Bixue Huang, Jincangjian Sun, Kaitian Chen
Summary: In this study, rare or novel gene mutations related to hearing loss were identified through genetic screening and pedigree mapping. Functional analysis and molecular modeling confirmed the damaging effects of these mutations on protein function. This study provides the first report of rare/novel mutations causing inherited hearing loss in the Chinese population.
MOLECULAR GENETICS & GENOMIC MEDICINE
(2022)
Article
Gastroenterology & Hepatology
Jodie Ouahed, Judith R. Kelsen, Waldo A. Spessott, Kameron Kooshesh, Maria L. Sanmillan, Noor Dawany, Kathleen E. Sullivan, Kathryn E. Hamilton, Voytek Slowik, Sergey Nejentsev, Joao Farela Neves, Helena Flores, Wendy K. Chung, Ashley Wilson, Kwame Anyane-Yeboa, Karen Wou, Preti Jain, Michael Field, Sophia Tollefson, Maiah H. Dent, Dalin Li, Takeo Naito, Dermot P. B. McGovern, Andrew C. Kwong, Faith Taliaferro, Jose Ordovas-Montanes, Bruce H. Horwitz, Daniel Kotlarz, Christoph Klein, Jonathan Evans, Jill Dorsey, Neil Warner, Abdul Elkadri, Aleixo M. Muise, Jeffrey Goldsmith, Benjamin Thompson, Karin R. Engelhardt, Andrew J. Cant, Sophie Hambleton, Andrew Barclay, Agnes Toth-Petroczy, Dana Vuzman, Nikkola Carmichael, Corneliu Bodea, Christopher A. Cassa, Marcella Devoto, Richard L. Maas, Edward M. Behrens, Claudio G. Giraudo, Scott B. Snapper
Summary: This study identified damaging variants in the STXBP3 gene in ten patients from five families with a unique clinical presentation of early onset IBD, bilateral sensorineural hearing loss, and recurrent infections. These mutations interfere with intracellular vesicular trafficking, leading to reduced STXBP3 protein expression and defects in cell polarity. Overall, this study highlights the critical role of STXBP3 in VEOIBD, sensorineural hearing loss, and immune dysregulation.
JOURNAL OF CROHNS & COLITIS
(2021)
Review
Biochemistry & Molecular Biology
Luc Boullaud, Helene Blasco, Thuy-Tran Trinh, David Bakhos
Summary: Sensorineural hearing loss is a common sensory deficit with various etiologies. Metabolomic studies may aid in developing objective tests and personalized treatment for hearing loss.
Article
Computer Science, Information Systems
Ziquan Zhu, Shui-Hua Wang
Summary: Breast cancer is a common malignant tumor in women, and its detection methods are inefficient. This paper proposes a network called ODET for breast cancer detection based on ultrasound images.
EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Hengde Zhu, Jian Wang, Shui-Hua Wang, Rajeev Raman, Juan M. Gorriz, Yu-Dong Zhang
Summary: This paper proposes an evolutionary attention-based network (EDCA-Net) for medical image classification tasks. The EDCA-Net outperforms state-of-the-art methods on three datasets and achieves comparable performance on the fourth dataset, demonstrating good generalizability for medical image classification.
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Shui-Hua Wang, Suresh Chandra Satapathy, Man-Xia Xie, Yu-Dong Zhang
Summary: COVID-19 is a single-stranded RNA virus, caused by the SARS-CoV-2 strain of coronavirus. This study proposes an ELU-based CNN model for COVID-19 diagnosis, achieving a sensitivity of 94.41 +/- 0.98, specificity of 94.84 +/- 1.21, accuracy of 94.62 +/- 0.96, and F1 score of 94.61 +/- 0.95. The ELUCNN model and mobile app are effective and outperform 14 state-of-the-art COVID-19 diagnosis models in terms of accuracy.
Article
Computer Science, Hardware & Architecture
Jiaji Wang, Shuihua Wang, Yudong Zhang
Summary: The eyes are crucial for human observation and perception, but visual impairment causes inconveniences in the lives of visually impaired individuals. Therefore, it is important to focus on their needs. Researchers are working to help visually impaired people live normal lives, using deep learning technology for the diagnosis of eye diseases and the development of visual aids. This paper summarizes recent research in these areas and provides an overview of how artificial intelligence can assist the visually impaired in the future.
Article
Physics, Multidisciplinary
Shuihua Wang, Ahmed M. S. E. K. Abdelaty, Kelly Parke, Jayanth Ranjit Arnold, Gerry P. McCann, Ivan Y. Tyukin
Summary: Myocardial infarction (MI) is a condition where the heart does not receive enough blood due to the blockage of a coronary artery. This study introduces an end-to-end automated system (MyI-Net) for the detection and quantification of MI in magnetic resonance images. The system utilizes four processing stages to extract features and perform image segmentation, showing improved performance compared to other methods.
Article
Green & Sustainable Science & Technology
Xianqing Chen, Wei Dong, Lingfang Yang, Qiang Yang
Summary: This paper proposes a scenario-based robust optimal planning solution for regional low-carbon integrated energy systems (IES), considering economic cost, carbon emissions, and energy supply reliability. The uncertainties of renewable power generation and various demands are addressed through a controllable generative adversarial network (GAN). A case study in China shows that the proposed capacity planning solution can reduce total cost by 4.24% and carbon emissions by 42.61%, confirming its effectiveness and benefits.
Article
Mathematics
Shtwai Alsubai, Abdullah Alqahtani, Adel Binbusayyis, Mohemmed Sha, Abdu Gumaei, Shuihua Wang
Summary: Early prediction and appropriate treatment of heart diseases are crucial for preventing complications and reducing mortality. Quantum learning improves accuracy and adaptability in detecting chronic diseases. This research compares quantum-based learning with traditional approaches using quantum machine learning and deep learning algorithms for disease prediction.
Article
Computer Science, Artificial Intelligence
Qinghua Zhou, Shuihua Wang, Hengde Zhu, Xin Zhang, Yudong Zhang
Summary: Deep ensemble learning, specifically multiple instance ensemble (MIE), is introduced as a novel stacking method for improving the performance of neural networks. By reformulating the ensemble learning process as a multiple-instance learning problem, MIE associates feature representations of base neural networks into joint representations using pooling operations. This study explores attention mechanisms and proposes new committee learning strategies with MIE. The capability of MIE to generate pseudo-base neural networks enables the creation of growing cascades. Experimental results on multiple HDLS datasets demonstrate the high performance of the proposed approach in low-sample size regime for binary classification tasks.
Article
Chemistry, Analytical
Anitha Rani Inturi, Vazhora Malayil Manikandan, Mahamkali Naveen Kumar, Shuihua Wang, Yudong Zhang
Summary: According to the World Health Organisation, falling is a major health problem with potentially fatal implications. Each year, thousands of people die as a result of falls, with seniors making up 80% of these fatalities. The automatic detection of falls may reduce the severity of the consequences. Our study focuses on developing a vision-based fall detection system using a new feature descriptor and body geometry analysis.
Article
Computer Science, Artificial Intelligence
Jianjian Yin, Zhichao Zheng, Yulu Pan, Yanhui Gu, Yi Chen
Summary: Semi-supervised semantic segmentation aims to classify pixels using both labeled and unlabeled images. The utilization of unlabeled images is crucial in semi-supervised learning. Existing methods tend to focus on reliable pixels while ignoring unreliable pixels, resulting in information loss. Uneven distribution of pixels per category can also lead to misclassification.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Review
Engineering, Multidisciplinary
Geng Chen, Lili Cheng, Rui Shao, Qingbin Wang, Shuihua Wang
Summary: With the advancement of urbanization, the issue of neurological diseases caused by population aging has become a global social concern. Aging leads to the deterioration of the central nervous system, shrinkage of brain tissue, and decline in physical function, making the elderly vulnerable to diseases like Alzheimer's, stroke, Parkinson's, and major depressive disorder. The impacts of these diseases include memory loss, mobility issues, and decreased quality of life. Therefore, tracking and real-time positioning of elderly individuals with neurological diseases are necessary for timely detection and treatment of emergencies. This paper presents an extensive survey of device-free indoor positioning technology for home-based care, analyzing current positioning systems, techniques, and technologies from the perspective of the needs of elderly patients. It also proposes evaluation criteria and potential solutions for positioning techniques in home-based care of neurologically impaired seniors, as well as discusses the opportunities and challenges in implementing indoor positioning technology in 6G mobile networks for this demographic.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Biology
Wei Wang, Yanrong Pei, Shui-Hua Wang, Juan Manuel Gorrz, Yu-Dong Zhang
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.
Review
Engineering, Multidisciplinary
Xiaoyan Jiang, Zuojin Hu, Shuihua Wang, Yudong Zhang
Summary: This paper introduces the latest methods and various techniques and algorithms of posture recognition, analyzes the general process and datasets, and compares several improved CNN methods and three main recognition techniques. Additionally, it discusses the applications of advanced neural networks in posture recognition and highlights the need for further research in feature extraction, information fusion, and data generation.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Review
Engineering, Multidisciplinary
Ziquan Zhu, Shui-Hua Wang, Yu-Dong Zhang
Summary: Breast cancer is a common type of cancer globally, and early diagnosis is crucial for improving treatment outcomes and survival rates. While CNN-based diagnosis methods have achieved great success, there are still limitations such as insufficient high-quality datasets, computationally intensive processes for large datasets, and potential overfitting with small datasets.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Multidisciplinary Sciences
Muhammad Attique Khan, Yu-Dong Zhang, Majed Alhusseni, Seifedine Kadry, Shui-Hua Wang, Tanzila Saba, Tassawar Iqbal
Summary: In this paper, a method for action recognition based on the fusion of shape and deep learning features is proposed. The method consists of two steps: human extraction and action recognition. By combining entropy-controlled feature selection and parallel conditional entropy approach, the features are fused and classified, achieving a high accuracy rate.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
