Area of research
Molecular Biology · Radiology, Nuclear Medicine and Imaging
Research interest
Research interests include Single-cell and spatial transcriptomics, Bioinformatics and Genomic Networks, Radiomics and Machine Learning in Medical Imaging, and Cancer Immunotherapy and Biomarkers.
Multi-center study on predicting breast cancer lymph node status from core needle biopsy specimens using multi-modal and multi-instance deep learning
A novel marker integrating multiple genetic alterations better predicts platinum sensitivity in ovarian cancer than HRD score
scBERT as a large-scale pretrained deep language model for cell type annotation of single-cell RNA-seq data
Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding
SOTIP is a versatile method for microenvironment modeling with spatial omics data
Phase II trial of efficacy, safety and biomarker analysis of sintilimab plus anlotinib for patients with recurrent or advanced endometrial cancer
Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep Learning
Screening of cell‐virus, cell‐cell, gene‐gene crosstalk among animal kingdom at single cell resolution
Multi-center study on predicting breast cancer lymph node status from core needle biopsy specimens using multi-modal and multi-instance deep learning
Multi-modal Multi-instance Learning Using Weakly Correlated Histopathological Images and Tabular Clinical Information
Camrelizumab Plus Apatinib in Patients With Advanced Cervical Cancer (CLAP): A Multicenter, Open-Label, Single-Arm, Phase II Trial
Predicting Lymph Node Metastasis Using Histopathological Images Based on Multiple Instance Learning With Deep Graph Convolution