A5063533847- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Renal cell carcinoma treatment
- CAR-T cell therapy research
- Cancer-related gene regulation
- Pancreatic and Hepatic Oncology Research
- Medical Imaging and Analysis
- Signaling Pathways in Disease
- Ferroptosis and cancer prognosis
- vaccines and immunoinformatics approaches
- Cancer Genomics and Diagnostics
Zhejiang University
2024-2025
First Affiliated Hospital Zhejiang University
2022-2025
Shanghai Clinical Research Center
2025
Zhejiang Cancer Hospital
2025
4019 Background: GPC3 is a surface antigen overexpressed in HCC and virtually absent on healthy tissues. Chimeric receptor (CAR) T cells targeting offer promising option for advanced unresectable treatment. C-CAR031 an autologous GPC3-directed CAR-T armored with dominant negative TGF-b II. Here we report the safety preliminary efficacy of patients (pts). Methods: The first-in-human, open-label dose-escalation trial employs accelerated titration plus i3+3 design. GPC3+ pts who failed ≥ 1 line...
Background: Integrating comprehensive information on hepatocellular carcinoma (HCC) is essential to improve its early detection. We aimed develop a model with multi-modal features (MMF) using artificial intelligence (AI) approaches enhance the performance of HCC Materials and methods: A total 1,092 participants were enrolled from 16 centers. These allocated into training, internal validation, external validation cohorts. Peripheral blood specimens collected prospectively subjected mass...
Hepatocellular carcinoma (HCC) is one of the most common cancers in world which ranks fourth cancer deaths. Primary pathological necrosis an effective prognostic indicator for hepatocellular carcinoma. We propose a GCN-based approach that mimics pathologist’s perspective global assessment tissue distribution to analyze patient survival. Specifically, we introduced graph convolutional neural network construct spatial map with necrotic and tumor as nodes, aiming mine contextual information...