Computational Intelligence
International Joint Conference, IJCCI 2016 Porto, Portugal, November 9–11, 2016 Revised Selected Papers
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Article
Open AccessAddressing data limitations in seizure prediction through transfer learning
According to the literature, seizure prediction models should be developed following a patient-specific approach. However, seizures are usually very rare events, meaning the number of events that may be used t...
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Article
Open AccessRemoving artefacts and periodically retraining improve performance of neural network-based seizure prediction models
The development of seizure prediction models is often based on long-term scalp electroencephalograms (EEGs) since they capture brain electrical activity, are non-invasive, and come at a relatively low-cost. Ho...
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Article
Open AccessUnsupervised EEG preictal interval identification in patients with drug-resistant epilepsy
Typical seizure prediction models aim at discriminating interictal brain activity from pre-seizure electrographic patterns. Given the lack of a preictal clinical definition, a fixed interval is widely used to ...
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Article
Open AccessEPIC: Annotated epileptic EEG independent components for artifact reduction
Scalp electroencephalogram is a non-invasive multi-channel biosignal that records the brain’s electrical activity. It is highly susceptible to noise that might overshadow important data. Independent component ...
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Article
Open AccessInterpretable EEG seizure prediction using a multiobjective evolutionary algorithm
Seizure prediction might be the solution to tackle the apparent unpredictability of seizures in patients with drug-resistant epilepsy, which comprise about a third of all patients with epilepsy. Designing seiz...
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Article
Open AccessHeart rate variability analysis for the identification of the preictal interval in patients with drug-resistant epilepsy
Electrocardiogram (ECG) recordings, lasting hours before epileptic seizures, have been studied in the search for evidence of the existence of a preictal interval that follows a normal ECG trace and precedes th...
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Article
Open AccessA personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction
Seizure prediction may improve the quality of life of patients suffering from drug-resistant epilepsy, which accounts for about 30% of the total epileptic patients. The pre-ictal period determination, characte...
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Article
Application of self-organizing map to identify nocturnal epileptic seizures
An approach to find the best patient-specific seizure detection system for nocturnal frontal lobe epilepsy (NFLE) is proposed. Data of several patients affected by NFLE, extracted from the European Epilepsy Da...
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Book and Conference Proceedings
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Article
Open AccessA knowledge discovery methodology from EEG data for cyclic alternating pattern detection
Detection and quantification of cyclic alternating patterns (CAP) components has the potential to serve as a disease bio-marker. Few methods exist to discriminate all the different CAP components, they do not ...
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Chapter and Conference Paper
Mixed-Integer Programming Model for Profiling Disease Biomarkers from Gene Expression Studies
Biomedical research has seen great advances in recent years, in great part due to the long-term aid of the ability to identify biological or genetic markers that uniquely match a given disease. Despite several...
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Book and Conference Proceedings
Computational Intelligence
Revised and Selected Papers of the International Joint Conference, IJCCI 2013, Vilamoura, Portugal, September 20-22, 2013
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Book and Conference Proceedings
Computational Intelligence
International Joint Conference, IJCCI 2014 Rome, Italy, October 22-24, 2014 Revised Selected Papers
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Chapter
Fuzzy Control as the Entrance Door to Control Theory
Control Systems have a more and more important role in our lives. The future of human kind depends largely on the space exploration, and autonomous intelligent controlled systems will be the key of its success...
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Chapter
Brainatic: A System for Real-Time Epileptic Seizure Prediction
A new system developed for real-time scalp EEG-based epileptic seizure prediction is presented, based on real time classification by machine learning methods, and named Brainatic. The system enables the consid...
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Chapter and Conference Paper
Overall Survival Prediction for Women Breast Cancer Using Ensemble Methods and Incomplete Clinical Data
Breast Cancer is the most common type of cancer in women worldwide. In spite of this fact, there are insufficient studies that, using data mining techniques, are capable of hel** medical doctors in their dai...
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Chapter and Conference Paper
A Tool for Biomedical – Documents Classification Using Support Vector Machines
This paper presents a web tool for text mining of biomedical literature using clustering and support vector machines. The study is specific to the domain of Peptidases, based on curated literature. It has been...
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Chapter and Conference Paper
A Platform for Peptidase Detection Based on Text Mining Techniques and Support Vector Machines
This paper presents a web platform for the detection of peptidases and motifs search from Merops database. The methodology for peptidases detection uses text mining techniques combined with Support Vector Mach...
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Chapter and Conference Paper
Efficient Discriminative Models for Proteomics with Simple and Optimized Features
The broad diversity in biology offers a panoply of interesting categorization problems for the machine learning community. New challenges arise in modern subjects such as protein classification, where huge and...
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Book and Conference Proceedings
Computational Intelligence
Revised and Selected Papers of the International Joint Conference, IJCCI 2011, Paris, France, October 24-26, 2011
