214 citations · 242 across the 4 of their papers we have counts for
5 papers
Towards Automatic Heart Murmur Characterization from Multi-spot Phonocardiograms
Marcelo Nogueira, Jorge H. Oliveira, Carlos G. Ferreira +2
Cardiac auscultation traditionally detects the presence of a heart murmur, but clinicians further characterize it by timing, shape, pitch, quality, and grade. Most automatic phonoc…
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…
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…
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…
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…