Andriana Susana Lopes de Oliveira Campanharo

• Abstract

  Alzheimer's disease (AD) can be understood as a degenerative and progressive dementia of the Central Nervous System. It is irreversible and with unknown cause. This disease is mainly characterized by a progressive intellectual deterioration, loss of memory and disorientation in time and space. AD is the leading dementia among older people over 65 and affects approximately 25 million indiv…

  Use of complex networks for the automatic detection, diagnosis and classification of the Alzheimer's Disease, AP.R
• 14th International Work-Conference on Artificial Neural Networks, AR.EXT
• NetSci 2014 International School and Conference on Network Science, AR.EXT

(Only some records are available in English at this moment)

• Abstract

  Epilepsy is defined as a neurological disorder of the brain that affects approximately 1% of the population. Clinically, epilepsy is characterized by spontaneous and recurrent crises, convulsive or non-convulsive, which are caused by partial or generalized discharges in the brain. Such convulsions are poorly controlled in more than 30% of epilepsy patients, and medical intervention is oft…

  The use of complex networks in the epileptogenic zone detection of epileptic patients, BP.IC

• Abstract

  Alzheimer's disease (AD), first characterized by the German neuropathologist Alois Alzheimer in 1907, can be understood as a degenerative and progressive dementia of the Central Nervous System, irreversible and that causes loss of memory and several cognitive disorders. AD is the leading dementia among older people over 65 and affects approximately 25 million individuals worldwide. Curren…

  Use of complex networks for the automatic detection and diagnosis of the Alzheimer's Disease, BP.IC

• Abstract

  Epilepsy is defined as a disorder of the brain characterized by a pre-disposition of producing convulsions. Such convulsions are poorly controlled in more than 30% of epilepsy patients, and medical intervention is often required. In most cases, the alternative is to remove the epileptogenic zone of the epileptic patient, that is, the neuronal region responsible for epileptic seizures. Bec…

  The use of complex networks in the seizures prediction and in the Epileptogenic Zone location of epileptic patients, BP.MS

(Only some records are available in English at this moment)

• Abstract

  Epilepsy is a brain disorder predominantly characterized by recurrent and unpredictable interruptions of the normal brain function, called as epileptic seizures. Epileptic seizures are episodes that can vary from brief and nearly undetectable to long periods of vigorous shaking. Such episodes can have a significant impact on the daily life of sufferers and are poorly controlled in more th…

  Automatic detection of the epileptogenic zone from EEG signals with the use of complex networks, BE.EP.MS

• Abstract

  Ecosystems are dynamic and change over time. Their evolution can be complex, non-linear and unpredictable, as it has been studied in the ecological literature. These characteristics are relevant to habitat management and forest restoration activities. Besides that, the ecosystems could present a potential for sudden changes and can be more vulnerable than expected. In order to analyze th…

  Computational modelling of the ecological succession of a direct seeding regeneration system via cellular automata, BE.EP.IC

• Abstract

  Epilepsy is a neurological disorder characterized by the presence of recurring seizures that affects nearly 1% of the general population. Sudden and abrupt seizures that cause momentarily lapses of consciousness can have significant impact on the daily life of sufferers. Thus, epileptic seizure detection would help these people to have a normal life. Recently, a map from time series to ne…

  Predicting epileptic seizures in EEG recordings with the use of complex networks, BE.EP.IC