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Details

  • Name

    Carlos Ferreira
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2010
002
Publications

2020

Improving Prediction with Causal Probabilistic Variables

Authors
Nogueira, AR; Gama, J; Ferreira, CA;

Publication
Advances in Intelligent Data Analysis XVIII - 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27-29, 2020, Proceedings

Abstract

2019

Classifying Heart Sounds Using Images of Motifs, MFCC and Temporal Features

Authors
Nogueira, DM; Ferreira, CA; Gomes, EF; Jorge, AM;

Publication
Journal of Medical Systems

Abstract

2019

Gait stride-to-stride variability and foot clearance pattern analysis in Idiopathic Parkinson's Disease and Vascular Parkinsonism

Authors
Ferreira, F; Gago, MF; Bicho, E; Carvalho, C; Mollaei, N; Rodrigues, L; Sousa, N; Rodrigues, PP; Ferreira, C; Gama, J;

Publication
Journal of Biomechanics

Abstract
The literature on gait analysis in Vascular Parkinsonism (VaP), addressing issues such as variability, foot clearance patterns, and the effect of levodopa, is scarce. This study investigates whether spatiotemporal, foot clearance and stride-to-stride variability analysis can discriminate VaP, and responsiveness to levodopa. Fifteen healthy subjects, 15 Idiopathic Parkinson's Disease (IPD) patients and 15 VaP patients, were assessed in two phases: before (Off-state), and one hour after (On-state) the acute administration of a suprathreshold (1.5 times the usual) levodopa dose. Participants were asked to walk a 30-meter continuous course at a self-selected walking speed while wearing foot-worn inertial sensors. For each gait variable, mean, coefficient of variation (CV), and standard deviations SD1 and SD2 obtained by Poincaré analysis were calculated. General linear models (GLMs) were used to identify group differences. Patients were subject to neuropsychological evaluation (MoCA test) and Brain MRI. VaP patients presented lower mean stride velocity, stride length, lift-off and strike angle, and height of maximum toe (later swing) (p < .05), and higher %gait cycle in double support, with only the latter unresponsive to levodopa. VaP patients also presented higher CV, significantly reduced after levodopa. Yet, all VaP versus IPD differences lost significance when accounting for mean stride length as a covariate. In conclusion, VaP patients presented a unique gait with reduced degrees of foot clearance, probably correlated to vascular lesioning in dopaminergic/non-dopaminergic cortical and subcortical non-dopaminergic networks, still amenable to benefit from levodopa. The dependency of gait and foot clearance and variability deficits from stride length deserves future clarification. © 2019 Elsevier Ltd

2019

Special track on data streams

Authors
Bifet, A; Carvalho, A; Ferreira, C; Gama, J;

Publication
Proceedings of the ACM Symposium on Applied Computing

Abstract

2019

Contrasting logical sequences in multi-relational learning

Authors
Ferreira, CA; Gama, J; Costa, VS;

Publication
Progress in Artificial Intelligence

Abstract
In this paper, we present the BeamSouL sequence miner that finds sequences of logical atoms. This algorithm uses a levelwise hybrid search strategy to find a subset of contrasting logical sequences available in a SeqLog database. The hybrid search strategy runs an exhaustive search, in the first phase, followed by a beam search strategy. In the beam search phase, the algorithm uses the confidence metric to select the top k sequential patterns that will be specialized in the next level. Moreover, we develop a first-order logic classification framework that uses predicate invention technique to include the BeamSouL findings in the learning process. We evaluate the performance of our proposals using four multi-relational databases. The results are promising, and the BeamSouL algorithm can be more than one order of magnitude faster than the baseline and can find long and highly discriminative contrasting sequences. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

Supervised
thesis

2019

Machine Learning para previsão de resultados de jogos de Ténis

Author
EDUARDO FILIPE SANTOS NOGUEIRA

Institution
IPP-ISEP

2019

Categorização de imagem aérea usando deep learning

Author
ALEXANDRE MANUEL SANTOS SILVA

Institution
IPP-ISEP

2019

Fog Computing

Author
NUNO TIAGO MELO GONÇALVES

Institution
IPP-ISEP

2018

Gestão de Conhecimento de uma Instituição de Educação

Author
JOSÉ EDUARDO BARREIRA CABEDA

Institution
IPP-ISEP