3 citations · 5 across the 5 of their papers we have counts for
5 papers
Beyond the Basics: Leveraging Large Language Model for Fine-Grained Medical Entity Recognition
Nwe Ni Win, Jim Basilakis, Steven Thomas +6
Extracting clinically relevant information from unstructured medical narratives such as admission notes, discharge summaries, and emergency case histories remains a challenge in cl…
MedVQA-TREE: A Multimodal Reasoning and Retrieval Framework for Sarcopenia Prediction
Pardis Moradbeiki, Nasser Ghadiri, Sayed Jalal Zahabi +3
Accurate sarcopenia diagnosis via ultrasound remains challenging due to subtle imaging cues, limited labeled data, and the absence of clinical context in most models. We propose Me…
Data Optimisation of Machine Learning Models for Smart Irrigation in Urban Parks
Nasser Ghadiri, Bahman Javadi, Oliver Obst +1
Urban environments face significant challenges due to climate change, including extreme heat, drought, and water scarcity, which impact public health, community well-being, and loc…
PerkwE_COQA: Enhanced Persian Conversational Question Answering by combining contextual keyword extraction with Large Language Models
Pardis Moradbeiki, Nasser Ghadiri
Smart cities need the involvement of their residents to enhance quality of life. Conversational query-answering is an emerging approach for user engagement. There is an increasing…
Multi-level biomedical NER through multi-granularity embeddings and enhanced labeling
Fahime Shahrokh, Nasser Ghadiri, Rasoul Samani +1
Biomedical Named Entity Recognition (NER) is a fundamental task of Biomedical Natural Language Processing for extracting relevant information from biomedical texts, such as clinica…