collaborators

6 papers

cs.CL2026

Towards Multidisciplinary Summarization of Hospital Stays: Efficient Sentence-Level Clinical Provenance Categorization

Baris Karacan, Vaibhav Bhargava, Barbara Di Eugenio +21

Effective "all-team" summarization in high-complexity settings like the Neonatal Intensive Care Unit (NICU) requires aggregating insights from diverse disciplines (physicians, nurs…

cs.CL2026

Early Risk Prediction with Temporally and Contextually Grounded Clinical Language Processing

Rochana Chaturvedi, Yue Zhou, Andrew D. Boyd +5

Clinical notes in Electronic Health Records (EHRs) capture rich temporal information on events, clinician reasoning, and lifestyle factors often missing from structured data. Lever…

cs.CL2026

Implicit Framing in Obstetric Counseling Notes: A Grounded LLM Pipeline on a VBAC-Eligible Cohort

Baris Karacan, Barbara Di Eugenio, Patrick Thornton +2

Clinical framing -- the linguistic manner in which clinical information is presented -- can influence patient understanding and decision-making, with important implications for hea…

cs.CL2025

Temporal Relation Extraction in Clinical Texts: A Span-based Graph Transformer Approach

Rochana Chaturvedi, Peyman Baghershahi, Sourav Medya +1

Temporal information extraction from unstructured text is essential for contextualizing events and deriving actionable insights, particularly in the medical domain. We address the…

cs.CL2025

Towards conversational assistants for health applications: using ChatGPT to generate conversations about heart failure

Anuja Tayal, Devika Salunke, Barbara Di Eugenio +5

We explore the potential of ChatGPT (3.5-turbo and 4) to generate conversations focused on self-care strategies for African-American heart failure patients -- a domain with limited…

cs.CL2025

Conversational Assistants to support Heart Failure Patients: comparing a Neurosymbolic Architecture with ChatGPT

Anuja Tayal, Devika Salunke, Barbara Di Eugenio +5

Conversational assistants are becoming more and more popular, including in healthcare, partly because of the availability and capabilities of Large Language Models. There is a need…