output
20202025
most citedThe CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification

214 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

11 papers

cs.CL2025★ 2 cited

Unraveling Emotions with Pre-Trained Models

Alejandro Pajón-Sanmartín, Francisco De Arriba-Pérez, Silvia García-Méndez +3

Transformer models have significantly advanced the field of emotion recognition. However, there are still open challenges when exploring open-ended queries for Large Language Model…

cs.IR2025

Identification and explanation of disinformation in wiki data streams

Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2

Social media platforms, increasingly used as news sources for varied data analytics, have transformed how information is generated and disseminated. However, the unverified nature…

cs.LG2024★ 2 cited

Online detection and infographic explanation of spam reviews with data drift adaptation

Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2

Spam reviews are a pervasive problem on online platforms due to its significant impact on reputation. However, research into spam detection in data streams is scarce. Another conce…

cs.CL2024★ 8 cited

Simulation, Modelling and Classification of Wiki Contributors: Spotting The Good, The Bad, and The Ugly

Silvia García Méndez, Fátima Leal, Benedita Malheiro +4

Data crowdsourcing is a data acquisition process where groups of voluntary contributors feed platforms with highly relevant data ranging from news, comments, and media to knowledge…

cs.CL2024★ 1 cited

Interpretable classification of wiki-review streams

Silvia García Méndez, Fátima Leal, Benedita Malheiro +1

Wiki articles are created and maintained by a crowd of editors, producing a continuous stream of reviews. Reviews can take the form of additions, reverts, or both. This crowdsourci…

cs.CL2024★ 5 cited

Exposing and Explaining Fake News On-the-Fly

Francisco de Arriba-Pérez, Silvia García-Méndez, Fátima Leal +2

Social media platforms enable the rapid dissemination and consumption of information. However, users instantly consume such content regardless of the reliability of the shared data…

q-bio.QM2022★ 27 cited

Beyond Heart Murmur Detection: Automatic Murmur Grading from Phonocardiogram

Andoni Elola, Elisabete Aramendi, Jorge Oliveira +6

Objective: Murmurs are abnormal heart sounds, identified by experts through cardiac auscultation. The murmur grade, a quantitative measure of the murmur intensity, is strongly corr…

cs.CL2022★ 25 cited

ZeroBERTo: Leveraging Zero-Shot Text Classification by Topic Modeling

Alexandre Alcoforado, Thomas Palmeira Ferraz, Rodrigo Gerber +5

Traditional text classification approaches often require a good amount of labeled data, which is difficult to obtain, especially in restricted domains or less widespread languages.…

cs.AI2021★ 3 cited

DEBACER: a method for slicing moderated debates

Thomas Palmeira Ferraz, Alexandre Alcoforado, Enzo Bustos +6

Subjects change frequently in moderated debates with several participants, such as in parliamentary sessions, electoral debates, and trials. Partitioning a debate into blocks with…

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…

eess.SP2020★ 1 cited

Segmentation and Optimal Region Selection of Physiological Signals using Deep Neural Networks and Combinatorial Optimization

Jorge Oliveira, Margarida Carvalho, Diogo Marcelo Nogueira +1

Physiological signals, such as the electrocardiogram and the phonocardiogram are very often corrupted by noisy sources. Usually, artificial intelligent algorithms analyze the signa…