Williams syndrome

Twite, Mark; Stenquist, Scott; Ing, Richard J.

doi:10.1111/pan.13620

Cited by 39 publications

(28 citation statements)

References 50 publications

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“…Williams syndrome is associated with mild to moderate intellectual disability and a distinct physical, cognitive and behavioural profile (Bellugi et al, 2000;Martens et al, 2008). Physical characteristics include cardiovascular disease, infantile hypercalcaemia, short stature and distinguishing facial features (Donnai & Karmiloff-Smith, 2000;Karmiloff-Smith et al, 2003;Morris & Mervis, 2000;Sindhar et al, 2016;Twite et al, 2019). Individuals with Williams syndrome often have developmental delay and specific cognitive impairments, particularly in the domain of visuospatial processing (Bellugi et al, 2000;Farran & Jarrold, 2003).…”

Section: Backg Rou N Dmentioning

confidence: 99%

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Anxiety characteristics in individuals with Williams syndrome

Royston

Oliver

Howlin

et al. 2021

Research Intellect Disabil

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Background: Williams syndrome anxiety research predominantly focuses on disorder prevalence and symptomatology, categorised using standardised mental health classifications. However, the use of these assessments may not fully capture the phenotypic features of anxiety in Williams syndrome. In this study, we examined characteristics of anxiety using a formulation framework.Method: A semi-structured interview was conducted with thirteen parents of individuals with Williams syndrome (median age: 19, age range: 12-45, 8 females).Results: Various anxiety triggers were reported, including anxiety triggered by phobias, uncertainty and negative emotions in others. The range of described behaviours was diverse with both avoidant and active coping strategies for anxiety management reported.Conclusions: Many of the characteristics described were consistent with findings in the intellectual disability and typically developing literature, although novel information was identified. The study demonstrates the utility of a formulation framework to explore anxiety characteristics in atypical populations and has outlined new avenues for research.

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Section: Backg Rou N Dmentioning

confidence: 99%

“…The behavioural phenotype includes impulsivity, short attention span, hypersociability, 'disruptive' behaviour and anxiety (Klein-Tasman & Lee, 2017;Ng-Cordell et al, 2018;Sampaio et al, 2018;Twite et al, 2019).…”

Section: Backg Rou N Dmentioning

confidence: 99%

Anxiety characteristics in individuals with Williams syndrome

Royston

Oliver

Howlin

et al. 2021

Research Intellect Disabil

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“…El 80% de los niños con SWB tienen anomalías cardiovasculares, siendo estas las principales causas de morbimortalidad [1,3,4]. La falta de elastina en las paredes de los vasos sanguíneos produce hiperplasia vascular del músculo liso que causa estrechez de la luz del vaso y estenosis arterial [3,4,10]. Las lesiones estenóticas son el sello distintivo del compromiso vascular en el primer año de vida; entre estas, la estenosis aórtica supravascular (EASV), que ocu-rre en el 55% de los casos, y la estenosis de la arteria pulmonar ramificada o periférica (EAP), en el 60% de los pacientes, como sucedió con el paciente del caso clínico, en quien se reportó estenosis pulmonar periférica derecha [4].…”

Section: Discussionunclassified

Síndrome de Williams-Beuren con estenosis pulmonar aislada: primer reporte de caso en el Cauca, Colombia

Realpe-Cisneros

Caicedo-Rodríguez

et al. 2021

Med. Lab.

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El síndrome de Williams-Beuren es una enfermedad congénita rara por microdeleción del cromosoma 7, que ocurre principalmente por una mutación de novo, y en menor frecuencia por herencia autosómica dominante. Se caracteriza por presentar alteraciones multisistémicas típicas, que incluyen apariencia facial de duendecillo, retraso del crecimiento y alteraciones neurológicas, como retraso mental y comportamiento hipersocial. Alrededor del 80% de los pacientes manifiestan anomalías cardiovasculares estructurales relacionadas con estenosis arterial aórtica o pulmonar. El objetivo de este reporte es presentar el primer caso de síndrome de Williams-Beuren en el departamento del Cauca, de un paciente de 24 meses de edad, atendido por el servicio de Genética Clínica en el Hospital Universitario San José de Popayán, en el cual el diagnóstico clínico se confirmó con el análisis molecular.

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“…The diagnosis of WBS often begins when astute clinicians recognize the specific facial dysmorphism. The characteristic facial gestalt of WBS is described as “cute” or “elfin” ( 3 ). Facial characteristics include broad forehead, periorbital puffiness, flat nasal bridge, short upturned nose, long philtrum, wide mouth, thick lips, and pointed chin ( 4 , 5 ).…”

Section: Introductionmentioning

confidence: 99%

Automatic Facial Recognition of Williams-Beuren Syndrome Based on Deep Convolutional Neural Networks

Liu

Yang

et al. 2021

Front. Pediatr.

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Background: Williams-Beuren syndrome (WBS) is a rare genetic syndrome with a characteristic “elfin” facial gestalt. The “elfin” facial characteristics include a broad forehead, periorbital puffiness, flat nasal bridge, short upturned nose, wide mouth, thick lips, and pointed chin. Recently, deep convolutional neural networks (CNNs) have been successfully applied to facial recognition for diagnosing genetic syndromes. However, there is little research on WBS facial recognition using deep CNNs.Objective: The purpose of this study was to construct an automatic facial recognition model for WBS diagnosis based on deep CNNs.Methods: The study enrolled 104 WBS children, 91 cases with other genetic syndromes, and 145 healthy children. The photo dataset used only one frontal facial photo from each participant. Five face recognition frameworks for WBS were constructed by adopting the VGG-16, VGG-19, ResNet-18, ResNet-34, and MobileNet-V2 architectures, respectively. ImageNet transfer learning was used to avoid over-fitting. The classification performance of the facial recognition models was assessed by five-fold cross validation, and comparison with human experts was performed.Results: The five face recognition frameworks for WBS were constructed. The VGG-19 model achieved the best performance. The accuracy, precision, recall, F1 score, and area under curve (AUC) of the VGG-19 model were 92.7 ± 1.3%, 94.0 ± 5.6%, 81.7 ± 3.6%, 87.2 ± 2.0%, and 89.6 ± 1.3%, respectively. The highest accuracy, precision, recall, F1 score, and AUC of human experts were 82.1, 65.9, 85.6, 74.5, and 83.0%, respectively. The AUCs of each human expert were inferior to the AUCs of the VGG-16 (88.6 ± 3.5%), VGG-19 (89.6 ± 1.3%), ResNet-18 (83.6 ± 8.2%), and ResNet-34 (86.3 ± 4.9%) models.Conclusions: This study highlighted the possibility of using deep CNNs for diagnosing WBS in clinical practice. The facial recognition framework based on VGG-19 could play a prominent role in WBS diagnosis. Transfer learning technology can help to construct facial recognition models of genetic syndromes with small-scale datasets.

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Williams syndrome

Cited by 39 publications

References 50 publications

Anxiety characteristics in individuals with Williams syndrome

Anxiety characteristics in individuals with Williams syndrome

Síndrome de Williams-Beuren con estenosis pulmonar aislada: primer reporte de caso en el Cauca, Colombia

Automatic Facial Recognition of Williams-Beuren Syndrome Based on Deep Convolutional Neural Networks

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