Publications by authors named "Hong-yu Kang"

Background And Objective: Transcranial sonography-based grading of Parkinson's Disease has gained increasing attention in recent years, and it is currently used for assistive differential diagnosis in some specialized centers. To this end, accurate midbrain segmentation is considered an important initial step. However, current practice is manual, time-consuming, and bias-prone due to the subjective nature.

View Article and Find Full Text PDF

Objective To develop a traceable cancer hallmark ontology with terminology including gene mutation,cancer hallmark,and cell line for knowledge integration,standardization,correlation,and discovery.Methods The Ontology Development 101 and the current ontology development methods were employed to determine the content coverage,structural layers,reusable terms,and new terms of the cancer hallmark ontology.Taking colorectal cancer as a study case,we extracted the knowledge related with colorectal cancer hallmarks using text mining and text classification technology from PubMed,and then formalized the extracted knowledge into the cancer hallmark ontology.

View Article and Find Full Text PDF
Article Synopsis
  • Biomedical technology is rapidly advancing, leading to exponential growth in data related to precision medicine, necessitating better ways to represent and integrate this scattered data.
  • The study aims to address key challenges in the precision medicine domain, including identifying primary entities, integrating biomedical vocabularies, and defining relationships among these entities through a semi-automated ontology development process.
  • The resulting Precision Medicine Ontology (PMO) encompasses 4.53 million terms across eleven categories, enriching the field with comprehensive coverage of crucial concepts like diseases and genes, and is publicly accessible for further research and use.
View Article and Find Full Text PDF

An effective classifier combining convolutional neural network and regularized extreme learning machine (called as CNN-RELM) is presented in this paper. Firstly, CNN-RELM trains the convolutional neural network (CNN) using the gradient descent method until the learning target accuracy reaches. Then the fully connected layer of CNN is replaced by regularized extreme learning machine (RELM) optimized by genetic algorithm and the rest layers of the CNN remain unchanged.

View Article and Find Full Text PDF

The aim of the study was to investigate the effect of chondroitinase ABC (ChABC) on ephrin A4 (EphA4) expression after spinal cord impairment (SCI) in rats. Adult female SD rats were randomly divided into three groups: ChABC group, normal saline (NS) group and sham group. In the ChABC and NS group, the SCI model was produced by the spinal cord hemisection.

View Article and Find Full Text PDF

Objective: To study the epidemiological status on rotavirus diarrhea in Kunming to improve the rotavirus vaccine immunization program.

Methods: A hospital-based sentinel surveillance program for rotavirus was set up among children less than 5 years old with acute diarrhea in Kunming Children's Hospital. Clinical information and fecal specimens were collected and rotavirus were detected by polyacrylamide gel electrophoresis (PAGE) and/or enzyme linked immunosorbent assay (ELISA).

View Article and Find Full Text PDF