scholarly journals Pilot Study on Analysis of Electroencephalography Signals from Children with FASD with the Implementation of Naive Bayesian Classifiers

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 103
Author(s):  
Katarzyna Anna Dyląg ◽  
Wiktoria Wieczorek ◽  
Waldemar Bauer ◽  
Piotr Walecki ◽  
Bozena Bando ◽  
...  
Keyword(s):  
Social Economic ◽  
Bayesian Classifiers ◽  
Eeg Signals ◽  
Fetal Alcohol ◽  
Helpful Tool ◽  
Naive Bayesian ◽  
Naïve Bayesian ◽  
The Social ◽  
Spectrum Disorders ◽  
Eeg Recordings

In this paper Naive Bayesian classifiers were applied for the purpose of differentiation between the EEG signals recorded from children with Fetal Alcohol Syndrome Disorders (FASD) and healthy ones. This work also provides a brief introduction to the FASD itself, explaining the social, economic and genetic reasons for the FASD occurrence. The obtained results were good and promising and indicate that EEG recordings can be a helpful tool for potential diagnostics of FASDs children affected with it, in particular those with invisible physical signs of these spectrum disorders.

On the Use of Naive Bayesian Classifiers for Detecting Elementary and Coordinated Attacks

2010 ◽  
Vol 105 (4) ◽  
pp. 435-466 ◽  
Author(s):  
Tayeb Kenaza ◽  
Karim Tabia ◽  
Salem Benferhat
Keyword(s):  
Bayesian Classifiers ◽  
Naive Bayesian ◽  
Naïve Bayesian

scholarly journals Understanding Fetal Alcohol Spectrum Disorders (FASDs): Toward Identification of a Behavioral Phenotype

2008 ◽  
Vol 8 ◽  
pp. 873-882 ◽  
Author(s):  
Kelly Nash ◽  
Erin Sheard ◽  
Joanne Rovet ◽  
Gideon Koren
Keyword(s):  
Review Paper ◽  
Fetal Alcohol Spectrum Disorders ◽  
Behavioral Phenotype ◽  
Future Research ◽  
Fetal Alcohol ◽  
The Social ◽  
Spectrum Disorders ◽  
Neurocognitive Profiles ◽  
Research Initiatives ◽  
Fetal Alcohol Spectrum

Fetal alcohol spectrum disorders (FASDs) currently represent the leading cause of mental retardation in North America, ahead of Down syndrome and cerebral palsy. The damaging effects of alcohol on the developing brain have a cascading impact on the social and neurocognitive profiles of affected individuals. Researchers investigating the profiles of children with FASDs have found impairments in learning and memory, executive functioning, and language, as well as hyperactivity, impulsivity, poor communication skills, difficulties with social and moral reasoning, and psychopathology. The primary goal of this review paper is to examine current issues pertaining to the identification of a behavioral phenotype in FASDs, as well as to address related screening and diagnostic concerns. We conclude that future research initiatives comparing children with FASDs to nonalcohol-exposed children with similar cognitive and socioemotional profiles should aid in uncovering the unique behavioral phenotype for FASDs.

Publishing naive Bayesian classifiers

2009 ◽  
Vol 2 (1) ◽  
pp. 1174-1185 ◽  
Author(s):  
Barzan Mozafari ◽  
Carlo Zaniolo
Keyword(s):  
Bayesian Classifiers ◽  
Naive Bayesian ◽  
Naïve Bayesian

Correlation Analysis in Classifiers

2010 ◽  
pp. 204-218
Author(s):  
Vincent Lemaire ◽  
Carine Hue ◽  
Olivier Bernier
Keyword(s):  
Correlation Analysis ◽  
General Framework ◽  
New Method ◽  
Classification Model ◽  
Data Sets ◽  
Bayesian Classifiers ◽  
Naive Bayesian ◽  
Naïve Bayesian ◽  
Predictive Probability ◽  
Input Variables

This chapter presents a new method to analyze the link between the probabilities produced by a classification model and the variation of its input values. The goal is to increase the predictive probability of a given class by exploring the possible values of the input variables taken independently. The proposed method is presented in a general framework, and then detailed for naive Bayesian classifiers. We also demonstrate the importance of “lever variables”, variables which can conceivably be acted upon to obtain specific results as represented by class probabilities, and consequently can be the target of specific policies. The application of the proposed method to several data sets shows that such an approach can lead to useful indicators.

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