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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(3)
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS(2)
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scopus(8)
Classification of hand movements from non-invasive brain signals using lattice neural networks with dendritic processing
Conference ObjectAbstract: EEG-based BCIs rely on classification methods to recognize the brain patterns that encode user’s intPalabras claves:Brain-Computer Interface, Electroencephalogram, Lattice Neural Network, Motor imageryAutores:Antelis J.M., Falcón-Morales L.E., Ojeda L., Roberto Vega, Sanchez-Ante G., Sossa H.Fuentes:scopusBlood vessel segmentation in retinal images using lattice neural networks
Conference ObjectAbstract: Blood vessel segmentation is the first step in the process of automated diagnosis of cardiovascularPalabras claves:Autores:Falcón-Morales L.E., Guevara E., Roberto Vega, Sanchez-Ante G., Sossa H.Fuentes:scopusFinding effective ways to (machine) learn fMRI-based classifiers from multi-site data
Conference ObjectAbstract: Machine learning techniques often require many training instances to find useful patterns, especiallPalabras claves:Batch effects, Machine learning, Multi-site fMRIAutores:Greiner R., Roberto VegaFuentes:scopusImproving pattern classification of DNA microarray data by using PCA and Logistic Regression
Conference ObjectAbstract: DNA microarrays is a technology that can be used to diagnose cancer and other diseases. To automatePalabras claves:DNA Microarray, Feature reduction, logistic regression, Principal Component AnalysisAutores:De Luna M.A., Falcón-Morales L.E., Ocampo-Vega R., Roberto Vega, Sanchez-Ante G., Sossa H.Fuentes:scopusIntegrating User-Input into Deep Convolutional Neural Networks for Thyroid Nodule Segmentation
Conference ObjectAbstract: Delineation of thyroid nodule boundaries is necessary for cancer risk assessment and accurate categoPalabras claves:deep learning, medical diagnosis, Thyroid nodule detection, Thyroid nodule tracking, Ultrasound image segmentationAutores:Daulatabad R., Hareendranathan A.R., Jaremko J.L., Kapur J., Punithakumar K., Roberto VegaFuentes:scopusRetinal vessel extraction using Lattice Neural Networks with dendritic processing
ArticleAbstract: Retinal images can be used to detect and follow up several important chronic diseases. The classificPalabras claves:Blood vessel segmentation, Dendritic processing, Diabetic Retinopathy, machine vision, Neural networks, pattern recognitionAutores:Falcón-Morales L.E., Guevara E., Roberto Vega, Sanchez-Ante G., Sossa H.Fuentes:scopusSIMLR: Machine Learning inside the SIR Model for COVID-19 Forecasting
ArticleAbstract: Accurate forecasts of the number of newly infected people during an epidemic are critical for makingPalabras claves:covid-19, interpretable machine learning, probabilistic graphical modelsAutores:Flores L., Greiner R., Roberto VegaFuentes:scopusThyroid Nodule Segmentation and Classification Using Deep Convolutional Neural Network and Rule-based Classifiers
Conference ObjectAbstract: Thyroid cancer has a high prevalence all over the world. Accurate thyroid nodule diagnosis can leadPalabras claves:Autores:Balachandran S., Forouzandeh A., Hareendranathan A.R., Jaremko J.L., Kapur J., Noga M., Punithakumar K., Roberto Vega, Shahroudnejad A.Fuentes:scopus