most citedEnhancing Clinical Efficiency through LLM: Discharge Note Generation for Cardiac Patients

7 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

Mitigating Adversarial Attacks in LLMs through Defensive Suffix Generation

Minkyoung Kim, Yunha Kim, Hyeram Seo +9

Large language models (LLMs) have exhibited outstanding performance in natural language processing tasks. However, these models remain susceptible to adversarial attacks in which s…

cs.CL2024

Multi-Response Preference Optimization with Augmented Ranking Dataset

Hansle Gwon, Imjin Ahn, Young-Hak Kim +2

Recent advancements in Large Language Models (LLMs) have been remarkable, with new models consistently surpassing their predecessors. These advancements are underpinned by extensiv…

cs.CL20247 cited

Enhancing Clinical Efficiency through LLM: Discharge Note Generation for Cardiac Patients

HyoJe Jung, Yunha Kim, Heejung Choi +10

Medical documentation, including discharge notes, is crucial for ensuring patient care quality, continuity, and effective medical communication. However, the manual creation of the…

cs.CV2024

InMD-X: Large Language Models for Internal Medicine Doctors

Hansle Gwon, Imjin Ahn, Hyoje Jung +3

In this paper, we introduce InMD-X, a collection of multiple large language models specifically designed to cater to the unique characteristics and demands of Internal Medicine Doc…

cs.CV20241 cited

NOTE: Notable generation Of patient Text summaries through Efficient approach based on direct preference optimization

Imjin Ahn, Hansle Gwon, Young-Hak Kim +2

The discharge summary is a one of critical documents in the patient journey, encompassing all events experienced during hospitalization, including multiple visits, medications, tes…