6 papers
DiagLink: A Dual-User Diagnostic Assistance System by Synergizing Experts with LLMs and Knowledge Graphs
Zihan Zhou, Yinan Liu, Yuyang Xie +3
The global shortage and uneven distribution of medical expertise continue to hinder equitable access to accurate diagnostic care. While existing intelligent diagnostic system have…
LLM/Agent-as-Data-Analyst: A Survey
Zirui Tang, Weizheng Wang, Zihang Zhou +16
Large language models (LLMs) and agent techniques have brought a fundamental shift in the functionality and development paradigm of data analysis tasks (a.k.a LLM/Agent-as-Data-Ana…
Characterization and Learning of Causal Graphs from Hard Interventions
Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
A fundamental challenge in the empirical sciences involves uncovering causal structure through observation and experimentation. Causal discovery entails linking the conditional ind…
Shiny-MAGEC: A Bayesian R Shiny Application for Meta-analysis of Censored Adverse Events
Zihan Zhou, Zizhong Tian, Christine B. Peterson +2
Accurate assessment of adverse event (AE) incidence is critical in clinical cancer research for drug safety evaluation and regulatory approval. While meta-analysis serves as an ess…
Research on the Proximity Relationships of Psychosomatic Disease Knowledge Graph Modules Extracted by Large Language Models
Zihan Zhou, Ziyi Zeng, Wenhao Jiang +7
As social changes accelerate, the incidence of psychosomatic disorders has significantly increased, becoming a major challenge in global health issues. This necessitates an innovat…
Sample Efficient Bayesian Learning of Causal Graphs from Interventions
Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu
Causal discovery is a fundamental problem with applications spanning various areas in science and engineering. It is well understood that solely using observational data, one can o…