activity
20112026
most citedThe CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification

214 citations · 282 across the 16 of their papers we have counts for

collaborators

18 papers

cs.LG2026

Selection of Heart Sound Segments for Synchronous Classification of Multi-channel Heart Sounds

Marcelo Nogueira, Jorge H. Oliveira, Carlos F. Ferreira +2

Cardiac auscultation remains the most cost-effective screening procedure for cardiovascular diseases, and requires listening at the four main auscultation spots. Despite this, auto…

cs.CL2024★ 1 cited

ACE-2005-PT: Corpus for Event Extraction in Portuguese

Luís Filipe Cunha, Purificação Silvano, Ricardo Campos +1

Event extraction is an NLP task that commonly involves identifying the central word (trigger) for an event and its associated arguments in text. ACE-2005 is widely recognised as th…

q-bio.QM2021★ 214 cited

The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification

Jorge Oliveira, Francesco Renna, Paulo Dias Costa +12

Cardiac auscultation is one of the most cost-effective techniques used to detect and identify many heart conditions. Computer-assisted decision systems based on auscultation can su…

cs.CL2021★ 5 cited

Improving Portuguese Semantic Role Labeling with Transformers and Transfer Learning

Sofia Oliveira, Daniel Loureiro, Alípio Jorge

The Natural Language Processing task of determining "Who did what to whom" is called Semantic Role Labeling. For English, recent methods based on Transformer models have allowed fo…

cs.IR2020

ECIR 2020 Workshops: Assessing the Impact of Going Online

Sérgio Nunes, Suzanne Little, Sumit Bhatia +11

ECIR 2020 https://ecir2020.org/ was one of the many conferences affected by the COVID-19 pandemic. The Conference Chairs decided to keep the initially planned dates (April 14-17, 2…

cs.CL2019★ 2 cited

Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation

Daniel Loureiro, Alipio Jorge

Contextual embeddings represent a new generation of semantic representations learned from Neural Language Modelling (NLM) that addresses the issue of meaning conflation hampering t…