A5100648787- AI in cancer detection
- Radiomics and Machine Learning in Medical Imaging
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Quantum Mechanics and Applications
- Colorectal Cancer Screening and Detection
- Digital Imaging for Blood Diseases
- Cryptography and Data Security
- Artificial Intelligence in Healthcare and Education
- Geographic Information Systems Studies
- Blockchain Technology Applications and Security
- Geological and Geochemical Analysis
- Lung Cancer Diagnosis and Treatment
- Geochemistry and Geologic Mapping
- Cancer Genomics and Diagnostics
- Privacy-Preserving Technologies in Data
- Image Retrieval and Classification Techniques
- Service-Oriented Architecture and Web Services
- Data Management and Algorithms
- Cervical Cancer and HPV Research
- Business Process Modeling and Analysis
- Complex Network Analysis Techniques
- Pancreatic and Hepatic Oncology Research
- IoT and Edge/Fog Computing
- Aquaculture Nutrition and Growth
State Ethnic Affairs Commission
2025
Yanbian University
2021-2025
Yanbian University Hospital
2025
UNSW Sydney
2022-2025
China-Japan Friendship Hospital
2025
Qingdao Agricultural University
2025
Yancheng Institute of Technology
2024
China University of Mining and Technology
2021-2024
Wuhan University
2022-2023
China University of Geosciences (Beijing)
2017-2023
The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden radiologists. In time an epidemic crisis, we hoped artificial intelligence (AI) to help reduce physician workload in regions with outbreak, and improve diagnosis accuracy for physicians before they could acquire enough experience new disease. Here, present our building deploying AI system that automatically analyzes CT images detect COVID-19 pneumonia features. Different from conventional medical AI,...
Abstract The early detection and accurate histopathological diagnosis of gastric cancer increase the chances successful treatment. worldwide shortage pathologists offers a unique opportunity for use artificial intelligence assistance systems to alleviate workload diagnostic accuracy. Here, we report clinically applicable system developed at Chinese PLA General Hospital, China, using deep convolutional neural network trained with 2,123 pixel-level annotated H&E-stained whole slide images....
Rechargeable zinc-air batteries afford great potential toward next-generation sustainable energy storage. Nevertheless, the oxygen redox reactions at air cathode are highly sluggish in kinetics to induce poor efficiency and limited cycling lifespan. Air cathodes with asymmetric configurations significantly promote electrocatalytic of loaded electrocatalysts, whereas rational synthetic methodology effectively fabricate remains insufficient. Herein, a strategy interface preconstruction is...
Abstract The electrocatalytic synthesis of multicarbon compounds from CO 2 is a promising method for storing renewable electricity and addressing global issues. Single‐atom catalysts are candidates reduction, but producing high‐value (C 2+ ) products using single‐atom structure remains significant challenge. In this study, fluorine doping strategy proposed to facilitate the reconstruction isolated Cu atoms, promoting generation. in situ formed nanocrystals contain substantial amount stable +...
Histopathology image analysis plays a critical role in cancer diagnosis and treatment. To automatically segment the cancerous regions, fully supervised segmentation algorithms require labor-intensive time-consuming labeling at pixel level. In this research, we propose CAMEL, weakly learning framework for histopathology using only image-level labels. Using multiple instance (MIL)-based label enrichment, CAMEL splits into latticed instances generates instance-level After labels are further...
Previous studies on deep learning (DL) applications in pathology have focused pathologist-versus-algorithm comparisons. However, DL will not replace the breadth and contextual knowledge of pathologists; rather, only through their combination may benefits be achieved. A fully crossed multireader multicase study was conducted to evaluate assistance with pathologists' diagnosis gastric cancer. total 110 whole-slide images (WSI) (50 malignant 60 benign) were interpreted by 16 board-certified...
This experiment was conducted to investigate the effects of dietary supplementation with marigold extract on growth performance, pigmentation, antioxidant capacity and meat quality in broiler chickens.A total 320 one-day-old Arbor Acres chickens were randomly divided into 5 groups 8 replicates each. The control group fed basal diet other experimental supplemented 0.075%, 0.15%, 0.30%, 0.60% respectively (the corresponding concentrations lutein 15, 30, 60, 120 mg/kg).The results showed that...
Abstract BACKGROUND The effects of dietary carnosine were evaluated on the growth performance, meat quality, antioxidant capacity and muscle fiber characteristics in thigh 256 one‐day‐old male broilers assigned to four diets – basal supplemented with 0, 100, 200 or 400 mg kg −1 respectively during a 42 day experiment. RESULTS Carnosine concentration synthase expression linearly increased ( P < 0.05) feed/gain ratio was decreased starter period by addition. Dietary supplementation resulted...
Objectives The microscopic evaluation of slides has been gradually moving towards all digital in recent years, leading to the possibility for computer-aided diagnosis. It is worthwhile know similarities between deep learning models and pathologists before we put them into practical scenarios. simple criteria colorectal adenoma diagnosis make it be a perfect testbed this study. Design model was trained by 177 accurately labelled training (156 with adenoma). detailed labelling performed on...
Background Histopathologic evaluation after surgery is the gold standard to evaluate treatment response neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). However, it cannot be used guide organ‐preserving strategies due poor timeliness. Purpose To develop and validate a multiscale model incorporating radiomics pathomics features for predicting pathological good (pGR) of down‐staging stage ypT0‐1N0 nCRT. Study Type Retrospective. Population A total 153 patients...
Jiawei Yanghe decoction (JWYHD) is a Traditional Chinese Medicine (TCM) formula for the treatment of osteoarthritis (OA), however underlying mechanisms action JWYHD in OA are not fully explored. This study investigates how protects cartilage from degradation via Wnt/β-catenin signaling pathway. The chondroprotective and anti-inflammatory effect on chondrocytes vitro MIA-induced rat model vivo were investigated. In vitro, increased chondrocyte viability against interleukin (IL)-1β-induced...
Abstract MicroRNAs (miRNAs) play crucial roles in multiple biological processes and human diseases can be considered as therapeutic targets of small molecules (SMs). Because experiments used to verify SM–miRNA associations are time-consuming expensive, it is urgent propose new computational models predict associations. Here, we proposed a novel method called Dual-network Collaborative Matrix Factorization (DCMF) for predicting the potential Firstly, utilized Weighted K Nearest Known...
Compared with histological examination of lung cancer, cytology is less invasive and provides better preservation complete morphology detail. However, traditional cytological diagnosis requires an experienced pathologist to evaluate all sections individually under a microscope, which time-consuming process low interobserver consistency. With the development deep neural networks, You Only Look Once (YOLO) object-detection model has been recognized for its impressive speed accuracy. Thus, in...
To achieve fast and accurate detection of wheat impurities, this study proposes an improved YOLOv8-based algorithm that targets three typical impurity types: bran, straw, spike. The original C2f module is replaced with the C2f_UIB structure from MobileNetV4 to reduce model complexity, a High-level Screening Feature Pyramid Network (HS-FPN) integrated enhance multi-scale feature fusion. Additionally, Generalized IoU loss function adopted improve robustness in dense scenarios. optimized...
We design a general framework named Hdoctor for hard drive failure prediction. leverages the power of big data to achieve significant improvement comparing all previous researches that used sophisticated machine learning algorithms. exhibits series engineering innovations: (1) constructing time dependent features characterize Self-Monitoring, Analysis and Reporting Technology (SMART) value transitions during disk failures, (2) combining enable model learn correlation among different SMART...
Given the high cost of large-scale data centers, an important design goal is to fully utilize available power resources maximize computing capacity. In this paper we present Ampere, a novel management system for centers increase capacity by over-provisioning number servers. Instead doing capping that degrades performance running jobs, use statistical control approach implement dynamic indirectly affecting workload scheduling, which can enormously reduce risk violations. being part already...
The accurate pathological diagnosis of endometrial cancer (EC) improves the curative effect and reduces mortality rate. Deep learning has demonstrated expert-level performance in a variety organ systems using whole-slide images (WSIs). It is urgent to build deep system for detection WSIs. model was trained validated dataset 601 WSIs from PUPH. tested on three independent datasets containing total 1,190 For retrospective test, we evaluated 581 In prospective study, 317 consecutive PUPH were...