Area of research
Cancer Research · Artificial Intelligence
Research interest
Research interests include Breast Cancer Treatment Studies, AI in cancer detection, Radiomics and Machine Learning in Medical Imaging, and HER2/EGFR in Cancer Research.
Chinese guidelines for HER2 testing in breast cancer (2024 edition): summary of key recommendations
A Study on Automatic O-RADS Classification of Sonograms of Ovarian Adnexal Lesions Based on Deep Convolutional Neural Networks
<b>Experts' </b><b>C</b><b>ognition-Driven Ensemble Deep Learning </b><b>f</b><b>or External Validation of Predicting Pathological Complete Response to Neoadjuvant Chemotherapy </b><b>f</b><b>rom Histological Images in Breast Cancer</b>
Exploratory study on the enhancement of O-RADS application effectiveness for novice ultrasonographers via deep learning
Combining the tumor-stroma ratio with tumor-infiltrating lymphocytes improves the prediction of pathological complete response in breast cancer patients
Near-Infrared II Hyperspectral Imaging Improves the Accuracy of Pathological Sampling of Multiple Cancer Types
336P Dual-mode near-infrared multispectral imaging system equipped with deep learning models improves the identification of cancer foci in breast cancer specimens
ERBB2 mRNA expression to distinguish HER2-low/neg breast cancer prognosis.
Dual-mode near-infrared multispectral imaging system equipped with deep learning models improves the identification of cancer foci in breast cancer specimens
CACA Guidelines for Holistic Integrative Management of Breast Cancer
Predicting neoadjuvant chemotherapy benefit using deep learning from stromal histology in breast cancer
Dual-mode near-infrared multispectral imaging system equipped with deep learning models improves the identification of cancer foci in breast cancer specimens
Near-infrared II hyperspectral imaging improves the accuracy of pathological sampling of multiple cancer specimens
How can artificial intelligence models assist PD-L1 expression scoring in breast cancer: results of multi-institutional ring studies
Improving Ki67 assessment concordance by the use of an artificial intelligence‐empowered microscope: a multi‐institutional ring study
Accurate Prognostic Prediction for Breast Cancer Based on Histopathological Images by Artificial Intelligence
Prediction model of the response to neoadjuvant chemotherapy in breast cancers by a Naive Bayes algorithm
Blind deblurring for microscopic pathology images using deep learning networks
[Research progress of biomarkers in breast phyllodes tumours].
Efficacy and safety of oral poly (ADP-ribose) polymerase inhibitor fluzoparib in patients with BRCA1/2 mutations and recurrent ovarian cancer
Immune Profiles of Tumor Microenvironment and Clinical Prognosis among Women with Triple-Negative Breast Cancer
Somatic alterations of <i>TP53</i>,<i> ERBB2</i>,<i> PIK3CA</i> and <i>CCND1</i> are associated with chemosensitivity for breast cancers
Hormone Receptor and Human Epidermal Growth Factor Receptor 2 Detection in Invasive Breast Carcinoma: A Retrospective Study of 12,467 Patients From 19 Chinese Representative Clinical Centers
Repression of miR-135b-5p promotes metastasis of early-stage breast cancer by regulating downstream target SDCBP
Screening of Recurrence Related MicroRNA in Ductal Carcinoma <i>In Situ</i> and Functional Study of MicroRNA-654-5p
Tamoxifen enhances stemness and promotes metastasis of ERα36+ breast cancer by upregulating ALDH1A1 in cancer cells
Whole exome and target sequencing identifies MAP2K5 as novel susceptibility gene for familial non‐medullary thyroid carcinoma
Long term prognosis of ductal carcinoma <i>in situ</i> with microinvasion: a retrospective cohort study.
PubMed 2018cited by 20position: last
A decision tree-based prediction model for fluorescence <i>in situ</i> hybridization <i>HER2</i> gene status in HER2 immunohistochemistry-2+ breast cancers: a 2538-case multicenter study on consecutive surgical specimens
Senescence of mesenchymal stem cells (Review)