Xingqiao Wang Source Confirmed

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

Researcher

University of Arkansas at Little Rock

faculty

9 h-index 45 pubs 331 cited

Research Areas

Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Natural Language Processing Techniques Bioinformatics and Genomic Networks Health and Medical Research Impacts Neuroscience and Neuropharmacology Research Cancer-related molecular mechanisms research

Links

ORCID Lab Website

Is this your profile? Verify and claim your profile

OverviewAI-generated summary

Xingqiao Wang's research focuses on the application of advanced computational frameworks, particularly those leveraging large language models (LLMs) and Transformer architectures, for causal inference in diverse domains. Wang has investigated the use of these models in pharmacovigilance, aiming to enhance patient safety by identifying potential adverse drug reactions and understanding drug effects. Publications include work on InferBERT, a Transformer-based causal inference framework for pharmacovigilance, and DeepCausality, an AI-powered framework for causal inference from free text with a case study on LiverTox. Further research explores LLMs for entity resolution and data linkage, demonstrated by the development of OmniMatch. Wang's work also extends to understanding molecular mechanisms in disease, with publications examining therapeutic targets for neuroinflammatory and tumorigenic processes, and the role of specific genes like WDR43 in preventing cerebral vasospasm and dementia. Wang has a h-index of 9 with 45 publications and 331 citations, and collaborates with researchers including Vivek Gunasekaran and Weida Tong.

Metrics

  • h-index: 9
  • Publications: 45
  • Citations: 331

Selected Publications

  • OmniMatch: A Large Language Model-Based Data Linkage Tool (2024) DOI
  • Train Once, Match Everywhere: Harnessing Generative Language Models for Entity Matching (2023) DOI
  • Bidirectional Encoder Representations from Transformers-like large language models in patient safety and pharmacovigilance: A comprehensive assessment of causal inference implications (2023) DOI
  • DeepCausality: A general AI-powered causal inference framework for free text: A case study of LiverTox (2022) DOI
  • InferBERT: A Transformer-Based Causal Inference Framework for Enhancing Pharmacovigilance (2021) DOI

Collaborators

Researchers in the database who share publications

Vivek Gunasekaran University of Arkansas at Little Rock 3 shared publications Weida Tong National Center for Toxicological Research 2 shared publications

Similar Researchers

Based on overlapping research topics

Farhan Kawsar University of Arkansas for Medical Sciences
Advanced Neural Network Applications Natural Language Processing Techniques Health and Medical Research Impacts
Good match 4 shared topics
R. E. Moore National Center for Toxicological Research
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Bioinformatics and Genomic Networks
Good match 4 shared topics
Joseph VanScoy University of Arkansas for Medical Sciences
Advanced Neural Network Applications Natural Language Processing Techniques Health and Medical Research Impacts
Good match 4 shared topics
Leihong Wu National Center for Toxicological Research
Advanced Neural Network Applications Pharmacological Effects and Toxicity Studies Natural Language Processing Techniques
Good match 4 shared topics
Nguyen Quoc Khanh Le University of Arkansas at Fayetteville
Advanced Neural Network Applications Natural Language Processing Techniques Bioinformatics and Genomic Networks
Good match 5 shared topics
Susan Gauch University of Arkansas at Fayetteville
Advanced Neural Network Applications Natural Language Processing Techniques Bioinformatics and Genomic Networks
Good match 4 shared topics