Mostrando 10 resultados de: 16
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2022 IEEE ANDESCON: Technology and Innovation for Andean Industry, ANDESCON 2022(3)
IFAC-PapersOnLine(3)
2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017(2)
2016 IEEE Ecuador Technical Chapters Meeting, ETCM 2016(1)
2017 4th International Conference on eDemocracy and eGovernment, ICEDEG 2017(1)
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Enfermedades(9)
Ciencias de la computación(8)
Fisiología humana(7)
Medicina y salud(4)
Cirugía y especialidades médicas afines(1)
Classification of subjects with parkinson's disease using finger tapping dataset
Conference ObjectAbstract: Parkinson's disease is the second most common neurodegenerative disorder and affects more than 7 milPalabras claves:classification, Finger Tapping, Machine learning, Parkinson's DiseaseAutores:Diego Hernán Peluffo-Ordóñez, Enrique Pelaez, Francis R. Loayza, Leandro L. Lorente-Leyva, Sanchez-Pozo N.N., Victor Asanza ArmijosFuentes:scopusClustering of EEG occipital signals using k-means
Conference ObjectAbstract: Recent studies show that it is feasible to use electrical signals from Electro-encephalography (EEG)Palabras claves:Butterworth Filter, Clusterization, Direct Current Artifacts, Electro-encephalography, Fast fourier transform, Occipital Lobe, Signal PreprocessingAutores:Carlos A. Salazar, Carmen Vaca-Ruiz, Christian Sacarelo, Enrique Pelaez, Francis R. Loayza, Kerly Ochoa, Victor Asanza ArmijosFuentes:googlescopusAutomatic Brain White Matter Hyperintensities Segmentation with Swin U-Net
Conference ObjectAbstract: This work proposes an automatic segmentation approach to detect White Matter Hyperintensities (WMH)Palabras claves:deep learning, segmentation, Swin-Transformer, WMHAutores:Bryan V. Piguave, Enrique Pelaez, Francis R. Loayza, José ViteriFuentes:googlescopusAutomatic brain white matter hypertinsities segmentation using deep learning techniques
Conference ObjectAbstract: White Matter Hyperintensities (WMH) are lesions observed in the brain as bright regions in Fluid AttPalabras claves:Convolutional neural network, U-net, WMH SegmentationAutores:Enrique Pelaez, Fabricio Layedra, Francis R. Loayza, José ViteriFuentes:googlescopusAnatomical Patterns Recognition of Impulse Control Disorders of Parkinsonian Patients Using Deep Learning of MRI structural images
Conference ObjectAbstract: In Parkinson's disease (PD) several neuropsychiatric conditions are highly frequent including impulsPalabras claves:deep learning, Impulsive Compulsive Disorders, MRI, PÁRKINSONAutores:Alexander Saravia, Enrique Pelaez, Francis R. Loayza, Jocellyn Luna, Obeso I., Victor Asanza ArmijosFuentes:googlescopusA Machine Learning-Based algorithm for the assessment of clinical metabolomic fingerprints in Zika virus disease
Conference ObjectAbstract: Data analysis for metabolomic studies is challenging considering the number of statistical tools andPalabras claves:logistic regression, Machine learning, PCa, SVM, Zika VirusAutores:Barrett M., Enrique Pelaez, Fernanda Bertuccez Cordeiro, Regato M., Washington Cardenas Medranda, Zambrano M.P.Fuentes:googlescopusA Pipeline for Segmenting and Classifying Brain Lesions Caused by Stroke: A Machine Learning Approach
Conference ObjectAbstract: Brain injuries caused by strokes are one of the leading causes of disability in the world. Current pPalabras claves:Artificial Intelligence, Brain injuries, Machine learning, strokeAutores:Alex Macas, Enrique Pelaez, Francis R. Loayza, Franco-Maldonado H., Roberto MenaFuentes:scopusA comparison of deep learning models for detecting COVID-19 in chest X-ray images
Conference ObjectAbstract: COVID-19 has spread around the world rapidly causing a pandemic. In this research, a set of Deep LeaPalabras claves:Convolutional neural network, covid-19, Machine learning, Transfer learning, X-Ray Image AnalysisAutores:Enrique Pelaez, Geancarlo Murillo, Ricardo Serrano, Washington B. CárdenasFuentes:scopusA voice analysis approach for recognizing Parkinson's disease patterns
Conference ObjectAbstract: Many of the patients diagnosed with Parkinson's disease (PD) do not know they have it until the mostPalabras claves:Machine learning, PÁRKINSON, Voice AnalysisAutores:Enrique Pelaez, Francis R. Loayza, Paucar G. Bryan, Yu Chen TaiFuentes:scopusDetection of Pathologies in X-Ray Chest Images using a Deep Convolutional Neural Network with Appropriate Data Augmentation Techniques
Conference ObjectAbstract: Current advances in trained Deep Learning models have allowed architectures, such as Convolutional NPalabras claves:Convolutional neural network, data augmentation, Data cleaning, deep learning, Pathology DetectionAutores:Enrique Pelaez, Federico X. Dominguez, Sebastián Quevedo-SacotoFuentes:googlescopus