Resilience in the Face of Fragile X Syndrome

2012 ◽  
Vol 22 (10) ◽  
pp. 1355-1368 ◽  
Author(s):  
Chantel L. Fourie ◽  
Linda C. Theron
2021 ◽  
Author(s):  
Toni Kasole Lubala ◽  
Tony Kayembe-Kitenge ◽  
Gerrye Mubungu ◽  
Aimé Lumaka ◽  
Gray Kanteng ◽  
...  

Abstract Background Computer-aided software such as the facial image diagnostic aid (FIDA) and Face2Gene has been developed to perform pattern recognition of facial features with promising clinical results. The aim of this study was to test Face2Gene's recognition performance on Bantu Congolese subjects with Fragile X syndrome (FXS) as compared to Congolese subjects with intellectual disability but without FXS (non-FXS). Method Frontal facial photograph from 156 participants (14 patients with FXS and 142 controls) were uploaded. Automated face analysis was conducted by using the technology used in proprietary software tools called Face2Gene CLINIC and Face2Gene RESEARCH (version 17.6.2). To estimate the statistical power of the Face2Gene technology in distinguishing affected individuals from controls, a cross validation scheme was used. Results The similarity seen in the upper facial region (of males and females) is greater than the similarity seen in other parts of the face. Binary comparison of FXS subjects versus subjects with ID negative for Fragile X syndrome and FXS subjects versus subjects with Down syndrome reveal an area under the curve values of 0.955 (p=0.002) and 0.986 (p=0.003). Conclusion The Face2Gene algorithm is separating well between FXS and Non-FXS subjects.


Author(s):  
◽  
Rebecca Schira ◽  
Samantha Alexander ◽  
Noelani Brisbane ◽  
Kaitlyn Williams
Keyword(s):  

Author(s):  
Decerie Mendoza ◽  
Tracy Ye ◽  
Martina Dualan ◽  
Elena Javier
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document