253 citations · 626 across the 18 of their papers we have counts for
7 papers · 1 filter
MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
Yilin Wen, Zifeng Wang, Jimeng Sun
Large language models (LLMs) have achieved remarkable performance in natural language understanding and generation tasks. However, they often suffer from limitations such as diffic…
Matching Patients to Clinical Trials with Large Language Models
Qiao Jin, Zifeng Wang, Charalampos S. Floudas +7
Patient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT…
Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
Xuan Zhang, Limei Wang, Jacob Helwig +60
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural sciences. Today, AI has started to advance natural sciences by improving, accelerating…
BIOT: Cross-data Biosignal Learning in the Wild
Chaoqi Yang, M. Brandon Westover, Jimeng Sun
Biological signals, such as electroencephalograms (EEG), play a crucial role in numerous clinical applications, exhibiting diverse data formats and quality profiles. Current deep l…
AutoTrial: Prompting Language Models for Clinical Trial Design
Zifeng Wang, Cao Xiao, Jimeng Sun
Clinical trials are critical for drug development. Constructing the appropriate eligibility criteria (i.e., the inclusion/exclusion criteria for patient recruitment) is essential f…
SPOT: Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning
Zifeng Wang, Cao Xiao, Jimeng Sun
Clinical trials are essential to drug development but time-consuming, costly, and prone to failure. Accurate trial outcome prediction based on historical trial data promises better…