Baoli Zhang

ORCID: 0000-0002-3664-0806
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About
Contact & Profiles
Research Areas
  • Natural Language Processing Techniques
  • Text and Document Classification Technologies
  • AI and HR Technologies
  • Extracellular vesicles in disease
  • Advanced Text Analysis Techniques
  • Competency Development and Evaluation
  • Complex Network Analysis Techniques
  • Topic Modeling
  • Employer Branding and e-HRM
  • RNA Interference and Gene Delivery
  • Advanced biosensing and bioanalysis techniques
  • Translation Studies and Practices
  • Lexicography and Language Studies

Zhejiang University
2025

Chinese Academy of Sciences
2021-2025

Institute of Biophysics
2025

First Affiliated Hospital Zhejiang University
2025

Institute of Automation
2021

Beijing University of Posts and Telecommunications
2019-2020

Beijing Language and Culture University
2015

RNA interference (RNAi) represents a promising gene-specific therapy against tumors. However, its clinical translation is impeded by poor performance of lysosomal escape and tumor targeting. This challenge especially prominent in glioblastoma (GBM) therapy, necessitating the penetration blood-brain barrier (BBB). Leveraging intrinsic tumor-targeting BBB traversing capability human H-ferritin, we designed series ferritin variants with positively charged cavity truncated carboxyl terminus,...

10.1126/sciadv.adr9266 article EN cc-by-nc Science Advances 2025-02-19

This paper describes our approach for the Chinese clinical named entity recognition (CNER) task organized by 2020 China Conference on Knowledge Graph and Semantic Computing (CCKS) competition. In this task, we need to identify boundary category labels of six entities from electronic medical record (EMR). We constructed a hybrid system composed semi-supervised noisy label learning model based adversarial training rule post-processing module. The core idea is reduce impact data noise...

10.1162/dint_a_00099 article EN Data Intelligence 2021-01-01

Competency analysis is the focus of attention in modern enterprise human resource management. Companies select right person to work position by matching competency requirements with employees. In order achieve this goal, paper uses a deep neural network implement text classifier. Through bi-LSTM and convolution structure, performance task significantly better than current mainstream classification method. other common tasks model can also good performance. At same time, creates Chinese...

10.1109/dsc.2019.00056 article EN 2019-06-01
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