Area of research
Molecular Biology · Computer Vision and Pattern Recognition
Research interest
Research interests include Face and Expression Recognition, Gene expression and cancer classification, Radiomics and Machine Learning in Medical Imaging, and Bioinformatics and Genomic Networks.
Collaborative Embedding Learning via Tensor Integration for Multi-View Clustering
Evolutionary route of nasopharyngeal carcinoma metastasis and its clinical significance
An Online Mammography Database with Biopsy Confirmed Types
DeepGA for automatically estimating fetal gestational age through ultrasound imaging
Two-Dimensional Unsupervised Feature Selection via Sparse Feature Filter
Accurate Multi-view Clustering by Exploiting Within-view High-order Affinities through Tensor Self-representation
Classification of COVID-19 by Compressed Chest CT Image through Deep Learning on a Large Patients Cohort
Automatic prediction of treatment outcomes in patients with diabetic macular edema using ensemble machine learning
DF-Net: Deep fusion network for multi-source vessel segmentation
Development and validation of a deep learning system to classify aetiology and predict anatomical outcomes of macular hole
Using deep‐learning algorithms to classify fetal brain ultrasound images as normal or abnormal
Computer-aided diagnosis for fetal brain ultrasound images using deep convolutional neural networks
Breast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital Mammograms
Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroups
Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning
Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services