DSpace Repository

Estimating the family bias to autism: a bayesian approach

Show simple item record

dc.creator CARVALHO, Emerson Assis de
dc.date.issued 2022-02-21
dc.identifier.uri https://repositorio.unifei.edu.br/jspui/handle/123456789/3193
dc.description.abstract Autism is an age- and sex-related lifelong neurodevelopmental condition characterized pri marily by persistent deficits in core domains such as social communication. It is estimated that ≈ 2% of children have some ASD trait. The autism etiology is mainly due to inherited genetic factors (>80%). The importance of early diagnosis and interventions motivated several studies involving groups at high risk for ASD, those with a greater predisposition to the disorder. Such studies are characterized by evaluating some characteristics of the individual itself or the family members of diagnosed individuals, mainly aiming to predict a future diagnosis or recurrence rates. One of the primary goals of Artificial Intelligence is to create artificial agents capable of intelligent behaviors, such as prediction problems. Prediction problems usually involve reasoning with uncertainty due to some information deficiency, in which the data may be imprecise or incorrect. Such solutions may seek the application of probabilistic methods to construct inference models. In this thesis, we will discuss the development of probabilistic networks capable of estimating the risk of autism among the family members given some evidence (e.g., other family members with ASD). In particular, the main novel contributions of this thesis are as follows: the proposal of some estimates regarding parents with ASD generating children with ASD; the highlight ing regarding the decrease in the ASD prevalence sex ratio among males and females when genetic factors are taken into account; the corroboration and quantification of past evidence that the clustering of ASD in families is primarily due to genetic factors; the computation of some estimates regarding the risk of ASD for parents, grandparents, and siblings; an estimate regarding the number of ASD cases in a family sufficient to attribute the ASD occurrences to the genetic inheritance; the assessment of some estimates for males and females individuals given evidence in grandparents, aunts-or-uncles, nieces-or nephews and cousins; and the proposition of some estimates indicating risk ranges for ASD by genetic similarity. pt_BR
dc.language eng pt_BR
dc.publisher Universidade Federal de Itajubá pt_BR
dc.rights Acesso Aberto pt_BR
dc.subject Autism spectrum disorder prevalence pt_BR
dc.subject Autism spectrum disorder etiology pt_BR
dc.subject Probabilistic graphical models pt_BR
dc.subject Bayesian networks pt_BR
dc.subject Markov models pt_BR
dc.title Estimating the family bias to autism: a bayesian approach pt_BR
dc.type Tese pt_BR
dc.date.available 2022-03-22
dc.date.available 2022-03-22T19:38:23Z
dc.date.accessioned 2022-03-22T19:38:23Z
dc.creator.Lattes http://lattes.cnpq.br/2565976082903026 pt_BR
dc.contributor.advisor1 BASTOS, Guilherme Sousa
dc.contributor.advisor1Lattes http://lattes.cnpq.br/1508015681115848 pt_BR
dc.publisher.country Brasil pt_BR
dc.publisher.department IESTI - Instituto de Engenharia de Sistemas e Tecnologia da Informação pt_BR
dc.publisher.program Programa de Pós-Graduação: Doutorado - Engenharia Elétrica pt_BR
dc.publisher.initials UNIFEI pt_BR
dc.subject.cnpq CNPQ::ENGENHARIAS::ENGENHARIA ELÉTRICA pt_BR
dc.relation.references CARVALHO, Emerson Assis de. Estimating the family bias to autism: a bayesian approach. 2022. 184 f. Tese (Doutorado em Engenharia Elétrica) – Universidade Federal de Itajubá, Itajubá, 2022. pt_BR


Files in this item

This item appears in the following Collection(s)

Show simple item record