A5100435342- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Neural and Behavioral Psychology Studies
- Functional Brain Connectivity Studies
- Muscle activation and electromyography studies
- Matrix Theory and Algorithms
- Neural Networks and Applications
- Anomaly Detection Techniques and Applications
- Hand Gesture Recognition Systems
- COVID-19 and Mental Health
- Nonlinear Differential Equations Analysis
- Blind Source Separation Techniques
- Nonlinear Partial Differential Equations
- Child and Adolescent Psychosocial and Emotional Development
- Face and Expression Recognition
- Guidance and Control Systems
- Human Pose and Action Recognition
- graph theory and CDMA systems
- Imbalanced Data Classification Techniques
- Advanced Mathematical Physics Problems
- Lung Cancer Treatments and Mutations
- COVID-19 epidemiological studies
- Robotic Path Planning Algorithms
- Metaheuristic Optimization Algorithms Research
- Health Systems, Economic Evaluations, Quality of Life
Nanjing Agricultural University
2025
Imperial College London
2003-2025
Shaanxi Provincial People's Hospital
2025
Institute of Disaster Prevention
2023-2025
Southwest University
2025
Chinese Academy of Agricultural Sciences
2024
Beijing Aerospace Flight Control Center
2016-2024
Sichuan University
2012-2024
Air Force Medical University
2022-2024
Wuhan University
2018-2024
The root causes of regional variation in medical spending are poorly understood and vary by clinical condition. To identify drivers for Medicare patients with advanced cancer, we used linked Surveillance, Epidemiology, End Results program (SEER)–Medicare data from the period 2004–10. We broke down into thirteen cancer-relevant service categories. then calculated contribution each category to variation. Acute hospital care was largest component chief driver variation, accounting 48 percent 67...
With the help of machine learning (ML) techniques, possible errors made by pathologists and physicians, such as those caused inexperience, fatigue, stress so on can be avoided, medical data examined in a shorter time more detailed manner. However, while conventional ML classification, achieved excellent performance classification accuracy when applied diagnoses, they have fatal shortcoming poor since imbalanced dataset, especially for detection minority category. To tackle shortcomings...
Automated segmentation of brain glioma plays an active role in diagnosis decision, progression monitoring and surgery planning. Based on deep neural networks, previous studies have shown promising technologies for segmentation. However, these approaches lack powerful strategies to incorporate contextual information tumor cells their surrounding, which has been proven as a fundamental cue deal with local ambiguity. In this work, we propose novel approach named Context-Aware Network (CANet)...
Depression is one of the most common mental health disorders, and a large number depressed people commit suicide each year. Potential depression sufferers usually do not consult psychological doctors because they feel ashamed or are unaware any depression, which may result in severe delay diagnosis treatment. In meantime, evidence shows that social media data provides valuable clues about physical conditions. this paper, we argue it feasible to identify at an early stage by mining online...
Abstract Breast cancer patients often have recurrence and metastasis after surgery. Predicting the risk of for a breast patient is essential development precision treatment. In this study, we proposed novel multi-modal deep learning prediction model by integrating hematoxylin & eosin (H&E)-stained histopathological images, clinical information gene expression data. Specifically, segmented tumor regions in H&E into image blocks (256 × 256 pixels) encoded each block 1D feature...
Background Proper function of the mammalian brain relies on establishment highly specific synaptic connections among billions neurons. To understand how complex neural circuits function, it is crucial to precisely describe neuronal connectivity and distributions synapses from individual Methods Findings In this study, we present a new genetic labeling method that expression presynaptic marker, synaptophysin-GFP (Syp-GFP) in neurons vivo. We assess reliability use analyze spatial patterning...
The longitudinal associations between popularity, overt aggression, and relational aggression were assessed in middle school high cohorts drawn from a large urban Northwest Chinese city. (n = 880; 13.33 years.) samples 841; 16.66 each followed for 2 years. In the concurrent regression analyses, was more strongly consistently associated with popularity than after controlling likability. Cross-lagged analyses revealed that predicted subsequent increases throughout whereas at 7th 10th grade 1...
In the field of natural language processing, rapid development large model (LLM) has attracted more and attention. LLMs have shown a high level creativity in various tasks, but methods for assessing such are inadequate. The assessment LLM needs to consider differences from humans, requiring multi-dimensional measurement while balancing accuracy efficiency. This paper aims establish an efficient framework LLMs. By adapting modified Torrance Tests Creative Thinking, research evaluates creative...
Scalp electroencephalogram (EEG), a recording of the brain's electrical activity, has been used to diagnose and detect epileptic seizures for long time. However, most researchers have implemented seizure detectors by manually hand-engineering features from observed EEG data, them in detection, which might not scale well new patterns seizures. In this paper, we investigate possibility utilising unsupervised feature learning, recent development deep automatically learn raw, unlabelled data...
<h3>Objectives</h3> To assess the relationship between social integration and physical mental health among humanitarian migrants (HMs) in Australia. <h3>Design, setting participants</h3> We used recently released first wave of data from 2013 ‘Building a New Life Australia’ survey, which is an ongoing nationwide longitudinal study. A total 2399 HMs participated survey. <h3>Main outcome measures</h3> Self-rated was measured using four items selected SF-36 generic measure status. The 6-item...
Automatic emotion recognition based on electroencephalo-graphic (EEG) signals has received increasing attention in recent years. The Deep Residual Networks (ResNets) can solve vanishing gradient problem and exploding well computer vision learn more profound semantic information. And for traditional methods, frequency features often play important role signal processing area. Thus, this paper, we use the pre-trained ResNets to extract deep information linear-frequency cepstral coefficients...
Abstract Background The outbreak of Corona Virus Disease (COVID-19) in 2019 has continued until now, posing a huge threat to the public’s physical and mental health, resulting different degrees health problems. As vulnerable segment public, anxiety is one most common problems among COVID-19 patients. Excessive aggravates psychological symptoms patients, which detrimental their treatment recovery, increases financial expenditure, affects family relations, adds medical burden. Objective This...
Previous work has shown that various symptoms of unilateral neglect, including the pathological shift subjective midline to right, may be improved by a short adaptation period prismatic visual field right. We report here improvement imagined neglect after prism exposure in patient with left neglect. Despite strong observed for mental images as well conventional tests, evocation left‐sided information from an internal image map France was fully recovered following This could not explained...
Abstract This study examined the characteristics associated with popularity and social preference in 769 14‐year‐old adolescents (54 percent boys) from mainland China. Consistent findings other countries, were moderately correlated overt aggression was positively but negatively preference. Prosocial behavior, athletic skill, dating, academic achievement, mutual friends both preference, effects for prosocial dating greater than The strong correlations between behavior are consistent Confucian...
The aim of this study was to prospectively evaluate the cognitive function, depression, anxiety, and sleep quality in patients with nasopharyngeal cancer (NPC) before after intensity-modulated radiotherapy (IMRT).Eligible newly diagnosed NPC treated primary IMRT were recruited. A series neuropsychological tests performed within 1 week IMRT. Cognitive function measured Das-Naglieri assessment system. Self-rating Anxiety Scale Depression used assess mood states. Sleep evaluated by means...
Stretchable sensors are promising in the field of wearable robotics. To date, it is still a challenge to design an artificial skin with thin and sensitive stretchable sensors. In this paper, we present new skin, SkinGest, integrating filmy strain machine learning algorithms for gesture recognition human hands. The presented sensor has sandwich structure consisting two elastomer layers on outside one soft electrode layer middle. Based improved fabrication process, make sensor's thickness down...