3 citations · 3 across the 8 of their papers we have counts for
11 papers
An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer
Mengxian Lyu, Cheng Peng, Tim Jang +18
Treatment planning in precision oncology requires synthesizing heterogeneous patient information with rapidly evolving clinical guidelines to ensure guideline-concordant care. Whil…
Prompt, Plan, Extract: Zero-Shot Agentic LLMs Workflows for Lung Pathology Extraction from Clinical Narratives
Aman Pathak, Cheng Peng, Mengxian Lyu +8
Information extraction from pathology reports is essential for cancer staging, tumor registry population. Yet key data remains embedded in narrative reports, making manual extracti…
Narrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure
Ziyi Chen, Mengyuan Zhang, Mustafa Mohammed Ahmed +4
Cancer treatments are known to introduce cardiotoxicity, negatively impacting outcomes and survivorship. Identifying cancer patients at risk of heart failure (HF) is critical to im…
Retrieval-Augmented LLMs for Evidence Localization in Clinical Trial Recruitment from Longitudinal EHR Narratives
Ziyi Chen, Mengxian Lyu, Cheng Peng +1
Screening patients for enrollment is a well-known, labor-intensive bottleneck that leads to under-enrollment and, ultimately, trial failures. Recent breakthroughs in large language…
Detecting HIV-Related Stigma in Clinical Narratives Using Large Language Models
Ziyi Chen, Yasir Khan, Mengyuan Zhang +7
Human immunodeficiency virus (HIV)-related stigma is a critical psychosocial determinant of health for people living with HIV (PLWH), influencing mental health, engagement in care,…
Improving Automatic Summarization of Radiology Reports through Mid-Training of Large Language Models
Mengxian Lyu, Cheng Peng, Ziyi Chen +3
Automatic summarization of radiology reports is an essential application to reduce the burden on physicians. Previous studies have widely used the "pre-training, fine-tuning" strat…