A5103250581- Radiomics and Machine Learning in Medical Imaging
- Advanced X-ray and CT Imaging
- Oil and Gas Production Techniques
- Drilling and Well Engineering
- AI in cancer detection
- Network Security and Intrusion Detection
- Autophagy in Disease and Therapy
- Medical Imaging and Analysis
- Security in Wireless Sensor Networks
- Advanced Image Fusion Techniques
- Big Data Technologies and Applications
- Brain Tumor Detection and Classification
- Grey System Theory Applications
- E-commerce and Technology Innovations
- Advanced Neural Network Applications
- Medical Imaging Techniques and Applications
- Tunneling and Rock Mechanics
- Thyroid Cancer Diagnosis and Treatment
- Lung Cancer Diagnosis and Treatment
- MicroRNA in disease regulation
- AI and Multimedia in Education
- Cardiac Valve Diseases and Treatments
- Advanced Image and Video Retrieval Techniques
- Immune cells in cancer
- Ovarian cancer diagnosis and treatment
Quanzhou Normal University
2021-2024
China National Petroleum Corporation (China)
2024
Third Affiliated Hospital of Harbin Medical University
2019-2024
Harbin Medical University
2015-2024
China University of Petroleum, Beijing
2022-2023
The accurate classification of Alzheimer's disease (AD) from MRI data holds great significance for facilitating early diagnosis and personalized treatment, ultimately leading to improved patient outcomes. To address this challenge, a comprehensive approach is proposed in study, which integrates advanced deep learning models. This study introduces an ensemble model AD classification, incorporates Soft-NMS into the Faster R–CNN architecture enhance candidate information merging improve...
Abstract Protein degradation is essential for maintaining protein homeostasis. The ubiquitin‒proteasome system (UPS) and autophagy–lysosome are the two primary pathways responsible directly related to cell survival. In malignant tumors, UPS plays a critical role in managing excessive load caused by cancer cells hyperproliferation. this review, we provide comprehensive overview of dual roles played autolysosome colorectal (CRC), elucidating their impact on initiation progression disease while...
Heart disease is a common affecting human health. Electrocardiogram (ECG) classification the most effective and direct method to detect heart disease, which helpful diagnosis of symptoms. At present, ECG depends on personal judgment medical staff, leads heavy burden low efficiency staff. Automatic analysis technology will help work relevant In this paper, we use MIT-BIH database extract QRS features signals by using Pan-Tompkins algorithm. After extraction samples, K-means clustering used...
Pelvic bone tumors represent a harmful orthopedic condition, encompassing both benign and malignant forms. Addressing the issue of limited accuracy in current machine learning algorithms for tumor image segmentation, we have developed an enhanced segmentation algorithm. This algorithm is built upon improved full convolutional neural network, incorporating fully network (FCNN-4s) conditional random field (CRF) to achieve more precise segmentation. The was employed conduct initial on...
Early diagnosis of intraperitoneal metastasis is a pivot for survival patients with serous epithelial ovarian cancers (SEOC). However, to date, there lack efficient molecular biomarker early SEOC. Here, we found that the expression chloride intracellular channel 1 (CLIC1) highly correlative metastasis. There very low CLIC1 in normal ovaries (NO), benign tumor (BOT), and primary cancer without (POCNM); but its remarkably high (POCM) omentum peritoneal Furthermore, clinic prediction SEOC,...
Background and Objective: Cardiovascular disease is a high-fatality health issue. Accurate measurement of cardiovascular function depends on precise segmentation physiological structure accurate evaluation functional parameters. Structural heart images calculation the volume different ventricular activity cycles form basis for quantitative analysis can provide necessary support clinical diagnosis, as well various cardiac diseases. Therefore, it important to develop an efficient algorithm....
Ovarian cancer is often accompanied by the production of ascites, and patients with repeated ascites are associated chemotherapy resistance. The previous study confirmed that ovarian who developed after had elevated autophagy levels in precipitated cells, which was positively correlated MDR1 expression blood patients.In order to explore correlation between chemoresistant, we searched TCGA GEO database analyze LC3B MDR1, identified targeting miRNA LC3B. It verified dual luciferase miR-204 can...
Automated segmentation methods for cardiac magnetic resonance imaging (MRI) offer valuable assistance in evaluating function clinical diagnosis. Nevertheless, prevailing techniques encounter challenges dealing with characteristics like indistinct image boundaries and uneven resolution MRI scans. Consequently, these often problems related to uncertainty within the same class of structures ambiguity when distinguishing between different classes. In our paper, enhancements are made U-Net model...
Due to its intricate nature and substantial data size, microscopic image of osteosarcoma often present a significant obstacle the effectiveness conventional retrieval methods. Therefore, this study investigates new approach for medical using advanced deep hashing techniques attention mechanisms address these challenges more effectively.
Abstract In oil and gas exploration, rate of penetration (ROP) is one the most important parameters that affect drilling costs performance. Therefore, prediction with accuracy has become an direction current work. order to solve problem existing models are not accurate enough predict ROP, this paper proposes ensemble learning approach called extreme gradient boosting (XGBoost) model. paper, in addition XGBoost model, different were constructed through various approaches, such as traditional...
Summary Subterranean oil and gas reserves are abundant, offering significant potential for exploration development. However, drilling often suffers from low efficiency due to the dense rock layers encountered. A major cause of this inefficiency is rapid wear bits, which significantly reduces their performance. This not only increases time spent on inefficient but also leads frequent bit changes, adding nonproductive time. Therefore, study focuses prediction widely used polycrystalline...
Segmenting and reconstructing 3D models of bone tumors from 2D image data is great significance for assisting disease diagnosis treatment. However, due to the low distinguishability surrounding tissues in images, existing methods lack accuracy stability. This study proposes a U-Net model based on double dimensionality reduction channel attention gating mechanism, namely DCU-Net oncological segmentation. After realizing automatic segmentation reconstruction osteosarcoma by optimizing feature...
With the rapid development of information technology era, era big data has also arrived. While computer networks are promoting prosperity and society, their applications have become more extensive in-depth. Smart city video surveillance systems entered an networked business integration. The problems endless. This article discusses network security in data, hoping to help strengthen our country. paper studies prevention strategies smart cities data.
Accurate identification of overflow fluid types facilitates timely and effective handling onsite accidents. Research into identifying the type is limited, there are only simple calculation models that do not consider enough effects; additionally, accuracy needs to be improved method perfect. If no drilling data, it impossible identify fluid. Therefore, this paper modifies density model by considering influence temperature, pressure field, two-phase flow model, making result more accurate...
In order to overcome the big error problem of false data location in traditional attack detection methods for sensor networks, this paper proposes a new method networks based on APIT algorithm. The range attacks is detected, and target node selected. Its vertex signal strength used compare it with neighbour node. algorithm determine whether attacked triangle, all overlapping area centroids available small areas are positions nodes complete attacks. experimental results show that accuracy...
Abstract With the rapid development of intelligent algorithm and image processing technology, limitations traditional methods are more obvious. Based on this, this paper studies a new pattern sparse representation optimization Gaussian mixture feature based convolution neural network, designs system model vehicle detection network. The data is collected from many aspects, network used for comprehensive analysis evaluation. can extract information better by making scheme real-time according...