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From the 1 of 5 linked papers with an AI index.

most citedNarrative Feature or Structured Feature? A Study of Large Language Models to Identify Cancer Patients at Risk of Heart Failure

3 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

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…

cs.CL2026

Exploring Post-Training Alignment of Small Language Models for Biomedical Data-to-Text Generation: A Case Study of Medication Leaflet

Xi Yang, Guodong Liu, Chuqin Li +10

The paper compares several post‑training alignment methods for small language models on the task of converting biomedical data into patient‑friendly medication leaflets, showing th…

cs.CL2026

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…

cs.LG20263 cited

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…

cs.LG2025

A Topic Modeling Analysis of Stigma Dimensions, Social, and Related Behavioral Circumstances in Clinical Notes Among Patients with HIV

Ziyi Chen, Yiyang Liu, Mattia Prosperi +5

Objective: To characterize stigma dimensions, social, and related behavioral circumstances in people living with HIV(PLWHs) seeking care, using NLP methods applied to a large colle…