4 papers · 1 filter
Plain language adaptations of biomedical text using LLMs: Comparision of evaluation metrics
Primoz Kocbek, Leon Kopitar, Gregor Stiglic
This study investigated the application of Large Language Models (LLMs) for simplifying biomedical texts to enhance health literacy. Using a public dataset, which included plain la…
UM_FHS at TREC 2024 PLABA: Exploration of Fine-tuning and AI agent approach for plain language adaptations of biomedical text
Primoz Kocbek, Leon Kopitar, Zhihong Zhang +3
This paper describes our submissions to the TREC 2024 PLABA track with the aim to simplify biomedical abstracts for a K8-level audience (13-14 years old students). We tested three…
Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare
Leon Kopitar, Primoz Kocbek, Lucija Gosak +1
This review examines the development of abstractive NLP-based text summarization approaches and compares them to existing techniques for extractive summarization. A brief history o…
Identifying and Decomposing Compound Ingredients in Meal Plans Using Large Language Models
Leon Kopitar, Leon Bedrac, Larissa J Strath +2
This study explores the effectiveness of Large Language Models in meal planning, focusing on their ability to identify and decompose compound ingredients. We evaluated three models…