3 citations · 3 across the 5 of their papers we have counts for
5 papers
Team Fusion@ SU@ BC8 SympTEMIST track: transformer-based approach for symptom recognition and linking
Georgi Grazhdanski, Sylvia Vassileva, Ivan Koychev +1
This paper presents a transformer-based approach to solving the SympTEMIST named entity recognition (NER) and entity linking (EL) tasks. For NER, we fine-tune a RoBERTa-based (1) t…
FMI@SU ToxHabits: Evaluating LLMs Performance on Toxic Habit Extraction in Spanish Clinical Texts
Sylvia Vassileva, Ivan Koychev, Svetla Boytcheva
The paper presents an approach for the recognition of toxic habits named entities in Spanish clinical texts. The approach was developed for the ToxHabits Shared Task. Our team part…
ExPe: Exact Positional Encodings for Generative Transformer Models with Extrapolating Capabilities
Aleksis Datseris, Sylvia Vassileva, Ivan Koychev +1
This paper introduces a novel approach to position embeddings in transformer models, named "Exact Positional Embeddings" (ExPE). An absolute positional embedding method that can ex…
Using LLMs for Multilingual Clinical Entity Linking to ICD-10
Sylvia Vassileva, Ivan Koychev, Svetla Boytcheva
The linking of clinical entities is a crucial part of extracting structured information from clinical texts. It is the process of assigning a code from a medical ontology or classi…
Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learning
Niccolò Marini, Stefano Marchesin, Lluis Borras Ferris +12
The increasing availability of biomedical data is helping to design more robust deep learning (DL) algorithms to analyze biomedical samples. Currently, one of the main limitations…