A5063182334- Advanced Radiotherapy Techniques
- Medical Imaging Techniques and Applications
- Lung Cancer Diagnosis and Treatment
- Radiomics and Machine Learning in Medical Imaging
- Animal Behavior and Welfare Studies
- Radiation Therapy and Dosimetry
- Advanced Computational Techniques and Applications
- Effects of Environmental Stressors on Livestock
- Smart Agriculture and AI
- Hepatocellular Carcinoma Treatment and Prognosis
- Meat and Animal Product Quality
- MRI in cancer diagnosis
- Breast Cancer Treatment Studies
- Head and Neck Cancer Studies
- Advanced X-ray and CT Imaging
- Brain Metastases and Treatment
- Remote Sensing and Land Use
- Glioma Diagnosis and Treatment
- Industrial Vision Systems and Defect Detection
- Environmental Changes in China
- Esophageal Cancer Research and Treatment
- Non-Destructive Testing Techniques
- Ideological and Political Education
- Technology and Security Systems
- Evolutionary Algorithms and Applications
Tianjin Agricultural University
2013-2025
Shandong First Medical University
2013-2025
Shandong Tumor Hospital
2013-2025
Shanghai Institute of Materia Medica
2022-2023
Chinese Academy of Sciences
2022-2023
University of Chinese Academy of Sciences
2022
Jimei University
2020
Chongqing Medical and Pharmaceutical College
2020
National Pingtung University
2020
Shenzhen Second People's Hospital
2020
Accurate identification of sheep is important for achieving precise animal management and welfare farming in large farms. In this study, a face detection method based on YOLOv3 model pruning proposed, abbreviated as YOLOv3-P the text. The used to identify pastures, reduce stress achieve farming. Specifically, we chose collect Sunit images from certain pasture Xilin Gol League Right Banner, Inner Mongolia, YOLOv3, YOLOv4, Faster R-CNN, SSD other classical target recognition algorithms train...
Background: The reproducibility and non-redundancy of radiomic features are challenges in accelerating the clinical translation radiomics. In this study, we focused on robustness extracted from computed tomography (CT) scans hepatocellular carcinoma (HCC) patients with respect to different tumor segmentation methods. Methods: Arterial enhanced CT images were retrospectively randomly obtained 106 patients. As a training data set, 26 HCC used calculate features' redundancy. Another set (55 25...
Glycolytic metabolism enzymes have been implicated in the immunometabolism field through changes metabolic status. PGK1 is a catalytic enzyme glycolytic pathway. Here, we set up high-throughput screen platform to identify inhibitors. DC-PGKI an ATP-competitive inhibitor of with affinity Kd = 99.08 nmol/L. stabilizes vitro and vivo, suppresses both activity kinase function PGK1. In addition, unveils that regulates production IL-1β IL-6 LPS-stimulated macrophages. Mechanistically, inhibition...
Determination of ovulation time is one the most important tasks in sow reproduction management. Temperature variation vulva sows can be used as a predictor time. However, skin temperatures existing studies are obtained manually from infrared thermal images, posing an obstacle to automatic prediction In this study, improved YOLO-V5s detector based on feature fusion and dilated convolution (FD-YOLOV5s) was proposed for extraction temperature images. For purpose reducing model complexity,...
In the published article [...]
Context Rice (Oryza sativa) panicle provides important information to improve production efficiency, optimise resources, and aid in successful breeding of high-performing rice varieties. Aims In order efficiently count panicles, a recognition model based on YOLOv5s-Slim Neck-GhostNet was evaluated. Methods We used the developmental stages from heading maturity as time period collect data for testing validating model. The GSConv convolution module YOLOv5 (You Only Look Once) compared with...
Detecting estrus in sows is important for improving pig reproductive performance and farm production efficiency levels. Traditional detection methods are highly subjective inaccurate, making it difficult to meet the demands of modern farming. This research developed a multimodal feature fusion method that combines audio thermal infrared image data enhance accuracy robustness monitoring breeding pigs. We designed Adaptive-PIG-OESTUS-CNN-ViT model, which uses images as inputs network model. By...
This study is aimed to develop and validate a machine learning model, which combined radiomics clinical characteristics predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC) patients. 204 advanced ESCC patients were included who underwent dCRT at our hospital. Patients randomly divided into training cohort validation with ratio of 7:3. The features selected by LASSO algorithm. multivariate logistics analysis (p < 0.05)....
The analysis was designed to compare dosimetric parameters among 3-D conformal radiotherapy (3DCRT), intensity-modulated (IMRT) and RapidArc (RA) identify which can achieve the lowest risk of radiation-induced liver disease (RILD) for hepatocellular carcinoma (HCC).Twenty patients with HCC were enrolled in this study. Dosimetric values 3DCRT, IMRT, RA calculated total dose 50 Gy/25 f. percentage normal volume receiving >40, >30, >20, >10, >5 Gy (V(40), V(30), V(20), V(10) V(5)) evaluated...
Current biochemical approaches have only identified the most well-characterized kinases for a tiny fraction of phosphoproteome, and functional assignments phosphosites are almost negligible. Herein, we analyze substrate preference catalyzed by specific kinase present novel integrated deep neural network model named FuncPhos-SEQ assignment human proteome-level phosphosites. incorporates phosphosite motif information from protein sequence using multiple convolutional (CNN) channels features...
To improve the classification of pig vocalization using vocal signals and recognition accuracy, a method based on multi-feature fusion is proposed in this study. With typical pigs large-scale breeding houses as research object, short-time energy, frequency centroid, formant first-order difference, Mel cepstral coefficient difference were extracted features. These features improved principal component analysis. A model with BP neural network optimized genetic algorithm was constructed. The...
Abstract Background Lung radiation injury is a critical complication of radiotherapy (RT) for thoracic esophageal carcinoma (EC). Therefore, the goal this study was to investigate feasibility and dosimetric effects reducing lung tissue irradiation dose during RT EC by applying volumetric modulated arc (VMAT) combined with active breathing control (ABC) moderate deep inspiration breath-hold (mDIBH). Methods Fifteen patients were randomly selected undergo two series computed tomography (CT)...
This study aimed to compare fixed-field, intensity-modulated radiotherapy (f-IMRT) with arc therapy (IMAT) treatment plans in dosimetry and practical application for cervical esophageal carcinoma. For ten carcinoma cases, f-IMRT plan (seven fixed-fields) two IMAT plans, namely RA (coplanar 360° arcs) RAx arcs without sectors from 80° 110°, 250° 280°), were generated. DVHs adopted the statistics of above parameters, as well conformal index (CI), homogeneity (HI), dose-volumetric parameters...
The aim of this study was to explore the characteristic 3DCT scanning phases and estimate comparative amount respiration motion information included in 4DCT by comparing volumetric positional difference between volumes from for radiotherapy non-small-cell lung cancer (NSCLC). A total 28 patients with NSCLC sequentially underwent simulation scans thorax during free breathing. images respiratory signal data were reconstructed sorted into 10 throughout a cycle. GTV-3D 3DCT, GTV-0%, GTV-20%,...