Leihong Wu Source Confirmed

Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.

High Impact

Staff Fellow

National Center for Toxicological Research

staff

24 h-index 109 pubs 2,298 cited

Research Areas

Advanced Neural Network Applications Natural Language Processing Techniques Cancer Genomics and Diagnostics Pharmacological Effects and Toxicity Studies Bioinformatics and Genomic Networks AI in cancer detection

Links

ORCID Research Group

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OverviewAI-generated summary

Leihong Wu's research focuses on the application of artificial intelligence (AI) and machine learning (ML) within regulatory science, with a particular emphasis on predictive toxicology and the analysis of biomedical data. Wu investigates methods to enhance the accuracy and interpretability of AI models used in toxicological assessments, utilizing large datasets such as those from the Tox21 program. This work includes exploring the trade-offs between prediction accuracy and model explainability.

Further research extends to the analysis of genomic sequencing data, particularly in the context of cancer diagnostics. Wu has contributed to studies evaluating the analytical validity of circulating tumor DNA (ctDNA) sequencing assays and developing best practices for cancer mutation detection using whole-genome and whole-exome sequencing. The application of natural language processing (NLP) techniques, including BERT-based models and ChatGPT, to analyze drug labeling documents for risk classification, such as identifying drug-induced liver injury, is also a key area of investigation.

Wu leads a research group and has a significant publication record, with 109 total publications and 2,298 citations, achieving an h-index of 24. Key collaborators include Joshua Xu, Magnus Gray, and Weida Tong from the National Center for Toxicological Research, as well as Donald J. Johann from the University of Arkansas for Medical Sciences.

Metrics

  • h-index: 24
  • Publications: 109
  • Citations: 2,298

Selected Publications

  • Comparative Study of Molecular Descriptors and AI-Based Embeddings for Toxicity Prediction (2025) DOI
  • Assessing the developmental effects of fentanyl and impacts on lipidomic profiling using neural stem cell models (2025) DOI
  • Biomarkers of Neurotoxicity and Disease (2025) DOI
  • Leveraging FDA Labeling Documents and Large Language Model to Enhance Annotation, Profiling, and Classification of Drug Adverse Events with AskFDALabel (2025) DOI
  • Is ChatGPT Ready for Public Use in Organ-Specific Drug Toxicity Research? (2025) DOI
  • Enhancing pharmacogenomic data accessibility and drug safety with large language models: a case study with Llama3.1 (2024) DOI
  • Description and Validation of a Novel AI Tool, LabelComp, for the Identification of Adverse Event Changes in FDA Labeling (2024) DOI
  • Assessing the performance of large language models in literature screening for pharmacovigilance: a comparative study (2024) DOI
  • SD-WEAT: Towards Robustly Measuring Bias in Input Embeddings (2024) DOI
  • Text summarization with ChatGPT for drug labeling documents (2024) DOI
  • PERform: assessing model performance with predictivity and explainability readiness formula (2024) DOI
  • A framework enabling LLMs into regulatory environment for transparency and trustworthiness and its application to drug labeling document (2024) DOI
  • RxBERT: Enhancing drug labeling text mining and analysis with AI language modeling (2023) DOI
  • Measurement and Mitigation of Bias in Artificial Intelligence: A Narrative Literature Review for Regulatory Science (2023) DOI
  • A Weakly Supervised Deep Learning Framework for Whole Slide Classification to Facilitate Digital Pathology in Animal Study (2023) DOI

Collaborators

Researchers in the database who share publications

Joshua Xu National Center for Toxicological Research 17 shared publications Magnus Gray National Center for Toxicological Research 8 shared publications Weida Tong National Center for Toxicological Research 7 shared publications Donald J. Johann University of Arkansas for Medical Sciences 4 shared publications Hong Fang National Center for Toxicological Research 4 shared publications Binsheng Gong National Center for Toxicological Research 3 shared publications William Slikker National Center for Toxicological Research 2 shared publications Dan Li National Center for Toxicological Research 2 shared publications

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