Xiang Wu

• Jilin University

Background With the rapid population aging in China, smart senior care is urgently demanded. Therefore, it is necessary to comprehensively consider people’s demand for smart senior care for its better development. This study aimed to explore the needs and expectations of relevant stakeholders of smart senior care in China in the context of active a...

With a growing security threat in wireless communication networks, a promising method for secure next-generation networks is a zero-trust framework focusing on authentication schemes. How to analyze the risks involved in authentication is a challenge. This study quantifies authentication risks within the zero-trust framework and introduces a privac...

Alzheimer's disease (AD) is a neurodegenerative ailment that is becoming increasingly common, making it a major worldwide health concern. Effective care depends on an early and correct diagnosis, but traditional diagnostic techniques are frequently constrained by subjectivity and expensive costs. This study proposes a novel Vision Transformer-equip...

Augmented Intelligence of Things (AIoT) combines augmented intelligence algorithms with the massive data collected by IoT devices, enabling more advanced decision-making. The typical application of AIoT is Edge Computing (EC), which provides computational and storage resources at the edge to support vehicle decision-making for computation tasks. Wi...

Aims To identify the risk factors associated with frailty among older adults in China and develop a predictive model for assessing their frailty risk. Design Secondary cross‐sectional analysis. Methods The 2018 Chinese Longitudinal Healthy Longevity Survey (CLHLS) provided data for this study. A total of 9006 participants were included in the ana...

With the increasing availability of diverse healthcare data sources, such as medical images and electronic health records, there is a growing need to effectively integrate and fuse this multimodal data for comprehensive analysis and decision-making. However, despite its potential, multimodal data fusion in healthcare remains limited. This review pa...

Background Bacterial image analysis plays a vital role in various fields, providing valuable information and insights for studying bacterial structural biology, diagnosing and treating infectious diseases caused by pathogenic bacteria, discovering and developing drugs that can combat bacterial infections, etc. As a result, it has prompted efforts t...

The surging popularity of virtual reality (VR) technology raises concerns about VR-induced motion sickness, linked to discomfort and nausea in simulated environments. Our method involves in-depth analysis of EEG data and user feedback to train a sophisticated deep learning model, utilizing an enhanced GRU network for identifying motion sickness pat...

Background Breast cancer remains a pressing global health concern, necessitating accurate diagnostics for effective interventions. Deep learning models (AlexNet, ResNet-50, VGG16, GoogLeNet) show remarkable microcalcification identification (>90%). However, distinct architectures and methodologies pose challenges. We propose an ensemble model, merg...

Background Maintaining machines effectively continues to be a challenge for industrial organisations, which frequently employ reactive or premeditated methods. Recent research has begun to shift its attention towards the application of Predictive Maintenance (PdM) and Digital Twins (DT) principles in order to improve maintenance processes. PdM tech...

Introduction Abusing antibiotic residues in the natural environment has become a severe public health and ecological environmental problem. The side effects of its biochemical and physiological consequences are severe. To avoid antibiotic contamination in water, implementing universal and rapid antibiotic residue detection technology is critical to...

Generative AI has become the focus of the intelligent education field, especially in the generation of personalized learning resources. Current learning resource generation methods recommend customized courses based on learning styles and interests, improving learning efficiency. However, these methods cannot generate personalized tutorials accordi...

Presents corrections to the article “A Tutorial-Generating Method for Autonomous Online Learning”.

Early detection of knee osteoarthritis is crucial because the damage in the knee joint is irreversible at the advanced stage. Medical images such as Magnetic Resonance Imaging plays an important role in knee osteoarthritis diagnosis as it provides excellent visualization of the osteoarthritis imaging biomarkers. Current clinical practice relies on...

Diabetes Retinopathy (DR) is the most common complication of Diabetes Mellitus and can lead to blindness if not detected early. Since DR is often asymptomatic in its early stage, timely diagnosis is crucial. Artificial Intelligence (AI) has the potential to facilitate early disease detection and treatment, but its implementation in the medical fiel...

Knee osteoarthritis (OA) is a prevalent musculoskeletal condition affecting millions worldwide, posing significant health and economic burdens. Characterized by the degeneration of joint cartilage, the progression of knee OA varies significantly among individuals, making its prediction a complex issue. Previous studies on automated knee OA diagnosi...

The increased utilization of virtual reality (VR) technology has raised concerns regarding VR-induced motion sickness, an adverse condition linked to discomfort and nausea within simulated environments. Our approach commenced with an extensive analysis of EEG data and subjective feedback obtained from users immersed in VR environments. This data se...

Since knee osteoarthritis is a 3D complexity, one of the most effective tools to diagnose this disease is through Magnetic Resonance Imaging (MRI). Due to the 3D nature of the MRI scans, different 3D deep learning models related to osteoarthritis diagnosis have been proposed, but they are mostly single-task models. This study aims to offer a comput...

Oil palm is a key agricultural resource in Malaysia. However, palm disease, most prominently basal stem rot caused at least RM 255 million of annual economic loss. Basal stem rot is caused by a fungus known as Ganoderma boninense. An infected tree shows few symptoms during early stage of infection, while potentially suffers an 80% lifetime yield lo...

Knee osteoarthritis is one of the most common musculoskeletal diseases and is usually diagnosed with medical imaging techniques. Conventionally, case identification using plain radiography is practiced. However, we acknowledge that knee osteoarthritis is a 3D complexity; hence, magnetic resonance imaging will be the ideal modality to reveal the hid...

Shigella and enterotoxigenic Escherichia coli (ETEC) are major bacterial pathogens of diarrheal disease that is the second leading cause of childhood mortality globally. Currently, it is well known that Shigella spp., and E. coli are very closely related with many common characteristics. Evolutionarily speaking, Shigella spp., are positioned within...

Raising older adults' frailty knowledge level and encouraging them to actively engage in the prevention and treatment of frailty is essential to promote healthy aging. This cross-sectional study investigated frailty knowledge level and its influencing factors in community-dwelling older adults in China. A total of 734 older adults were included in...

Alzheimer's disease (AD) is a neurodegenerative disorder that causes memory degradation and cognitive function impairment in elderly people. The irreversible and devastating cognitive decline brings large burdens on patients and society. So far, there is no effective treatment that can cure AD, but the process of early-stage AD can slow down. Early...

Assistive technology for the differently abled and older adults has made remarkable achievements in providing rehabilitative, adaptive, and assistive devices. It provides huge assistance for people with physical impairments to lead a better self-reliant daily life, in terms of mobility, education, rehabilitation, etc. This technology ranges from si...

Deep learning, particularly Convolutional Neural Networks, has demonstrated effectiveness in computer-aided diagnosis applications, including knee osteoarthritis analysis. Two of the most common tasks done in medical imaging are the segmentation and classification tasks. This research investigates the feasibility of multi-task models for volumetric...

Abstract Background Population aging has become an escalating issue in China resulting in increasing healthcare demand. Smart senior care has the potential to help older adults live independently and relieve the pressure of healthcare including home-based care. This study aimed to explore Chinese older adults’ preferred access models and service co...

Background The importance of strategies and services by caregivers and family members substantially impact the psychological and emotional wellbeing of autistic children. The rapid research developments in clinical and non-clinical methods benefit the features of autistic children. Among various internal and external factors, the influence of the b...

Background Raising older adults’ frailty knowledge level and encouraging them to actively engage in the prevention and treatment of frailty is important to promote healthy aging. This study aimed to investigate frailty knowledge level and its influencing factors among community-dwelling older adults in China. Methods This cross-sectional study inc...

Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model is crucial for detecting complex disease gene-type and predicting pathogenic genes of various disorders. We present a novel framework for high-order gene interactions detection, not directly identifying individual site, but based on Deep Learning (DL)...

The purpose of Genome-Wide Association Studies (GWAS) is to find various variations in human disorders and have become one of the most commonly-used methods to find the pathogenesis and genetic mechanisms of complex diseases. However, in the GWAS process, it needs to frequently search the genome-wide data, especially in the calculation process of m...

Sensors play an important role in shaping and monitoring human health. Exploration of methods to use Fiber Bragg Grating (FBG) with enhanced sensitivity has attracted great interest in the field of medical research. In this paper, a novel apodization function is proposed and performance evaluation and optimization of the same have been made. A comp...

Workplace accidents can cause a catastrophic loss to the company including human injuries and fatalities. Occupational injury reports may provide a detailed description of how the incidents occurred. Thus, the narrative is a useful information to extract, classify and analyze occupational injury. This study provides a systematic review of text mini...

Caching and artificial intelligence technology are means to improve the content transmission rate and solve the delay problem in heterogeneous communication networks, which provide an important technical basis for telemedicine diagnosis, disease monitoring, and other medical and healthcare fields. However, since the data used for caching recommenda...

One of the primary factors contributing to death across all age groups is cardiovascular disease. In the analysis of heart function, analyzing the left ventricle (LV) from 2D echocardiographic images is a common medical procedure for heart patients. Consistent and accurate segmentation of the LV exerts significant impact on the understanding of the...

How to transform the growing medical big data into medical knowledge is a global topic. However, medical data contains a large amount of personal privacy information, especially electronic medical records, gene data and electroencephalography data; the current methods and tools for data sharing are not efficient or cannot be applied in real-life ap...

The amalgamation of the Internet of medical things with artificial intelligence shows tremendous benefits in health care. Accurate detection of the fetal QRS complex is highly demanded in fetal heart rate monitoring. Detecting fetal heart rate using electrophysiological signals obtained from abdominal electrodes seems a promising alternative approa...

Objective Deep learning algorithms have long been involved in the diagnosis of severe neurological disorders that interfere with patients’ everyday tasks, such as Parkinson’s disease (PD). The most effective imaging modality for detecting the condition is DaTscan, a variety of single-photon emission computerized tomography (SPECT) imaging method. T...

Alzheimer’s disease (AD) is an irreversible neurological disorder that affects the vast majority of dementia cases, leading patients to experience gradual memory loss and cognitive function decline. Despite the lack of a cure, early detection of Alzheimer’s disease permits the provision of preventive medication to slow the disease’s progression. Th...

Intraoperative neuromonitoring (IONM) has been used to help monitor the integrity of the nervous system during spine surgery. Transcranial motor-evoked potential (TcMEP) has been used lately for lower lumbar surgery to prevent nerve root injuries and also to predict positive functional outcomes of patients. There were a number of studies that prove...

Plaque deposits in the carotid artery are the major cause of stroke and atherosclerosis. Ultrasound imaging is used as an early indicator of disease progression. Classification of the images to identify plaque presence and intima-media thickness (IMT) by machine learning algorithms requires features extracted from the images. A total of 361 images...

Mining the core value of Industrial Internet of Things (IIoT) data safely and reducing the risk of malicious attacks are the inherent requirements of industrial data visualization. Visualization technology has become the main tool for data aggregation, mining and analysis of IIoT data through graphical representation. However, visualization technol...

Infectious diseases pose a serious threat to human life, the Genome Wide Association Studies (GWAS) can analyze susceptibility genes of infectious diseases from the genetic level and carry out targeted prevention and treatment. The susceptibility genes for infectious diseases often act in combination with multiple susceptibility sites; therefore, h...

Analyzing K-order Single Nucleotide Polymorphism (SNP) interactions through the statistics of Genome-Wide Association Studies (GWAS) is crucial for discovering pathogenic causes of human complex diseases and controlling risk genetic variants of diverse disorders. We propose a method based on Ant Colony Optimization (ACO) algorithm to detect gene...

Spectral clustering is a widely used clustering algorithm based on the advantages of simple implementation, small computational cost, and good adaptability to arbitrarily shaped data sets. However, due to the lack of data protection mechanism in spectral clustering algorithm and the fact that the processed data often contains a large amount of sens...

Objective Medical data mining and sharing is an important process in E-Health applications. However, because these data consist of a large amount of personal private information of patients, there is the risk of privacy disclosure when sharing and mining. Therefore, ensuring the security of medical big data in the process of publishing, sharing, an...

Driven by the upcoming development of the sixth-generation communication system (6G), the distributed machine learning schemes represented by federated learning has shown advantages in data utilization and multi-party cooperative model training. The total communication costs of federated learning is related to the number of communication rounds, th...

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume a...

Predicting virtual machine (VM) workload to realize dynamic allocation resources has always been a hot issue in research, most of the current resource prediction methods are based on different load resources to build prediction models, it is difficult to realize knowledge transfer between multi-task prediction models to complete multiple tasks’ pre...

BACKGROUND Medical data mining and sharing is an important process to realize the value of medical big data in E-Health applications. However, medical data contains a large amount of personal private information of patients, there is a risk of privacy disclosure when sharing and mining. Therefore, how to ensure the security of medical big data in t...

DNA motif finding is an important study to understand the regulation of gene expression, however, the existing methods generally ignore the potential sensitive information that may be exposed in the process. In this work, we utilize the differential privacy model to provide provable privacy guarantees which is independent of attackers? background k...

As one of the most commonly used types of application, command line applications have aroused extensive attention. Predicting command line application workload and providing reasonable resource scheduling strategy can effectively improve resource utilization and performance of VMs. This paper provided a novel scheme with two-level hybrid adaptive m...

DNA sequence analysis plays an important role in the study of gene regulatory networks. DNA motif finding has become a key discipline in the post-gene era and gradually become a research hotspot by mining key gene sequences corresponding to disease mechanism and important biological functions. However, the research of DNA motif finding is faced wit...

Biomedical data can be de-identified via micro-aggregation achieving k-anonymity privacy. However, the existing micro-aggregation algorithms result in low similarity within the equivalence classes, and thus, produce low-utility anonymous data when dealing with a sparse biomedical dataset. To achieve high utility, we propose a density-based second d...

As one of the basic research methods of bioinformatics, DNA motif finding is of great significance to the study of mechanisms for regulating gene expression and the discovery of biological functional sites. However, because of the high sensitivity of DNA data, the privacy disclosure of these data during motif finding has become a bottleneck in the...

Energy storage compounds play crucial roles in prokaryotic physiology. Five chemical compounds have been identified in prokaryotes as energy reserves: polyphosphate (polyP), polyhydroxyalkanoates (PHAs), glycogen, wax ester (WE) and triacylglycerol (TAG). Currently, no systematic study of archaeal energy storage metabolism exists. In this study, we...

In bacteria, glycogen plays important roles in carbon and energy storage. Its structure has recently been linked with bacterial environmental durability. Among the essential genes for bacterial glycogen metabolism, the glgB-encoded branching enzyme GBE plays an essential role in forming α-1,6-glycosidic branching points, and determines the unique b...

In order to address the bottleneck problem of low fine-particle removal efficiency of self-excited dust scrubbers, this paper is focused on the influence of the intermittent gas-liquid two-phase flow on the mesoscale behavior of collector aggregations. The latter is investigated by the application of high-speed dynamic image technology to the self-...

Multimodal medical image fusion plays a vital role in clinical diagnoses and treatment planning. In many image fusion methods-based pulse coupled neural network (PCNN), normalized coefficients are used to motivate the PCNN, and this makes the fused image blur, detail loss, and decreases contrast. Moreover, they are limited in dealing with medical i...