Fetal alcohol spectrum disorders FASDs are a group of conditions that can occur in a person whose mother drank alcohol during their pregnancy. Fetal alcohol spectrum disorders are caused by drinking alcohol during pregnancy. Fetal alcohol spectrum disorders are preventable by avoiding alcohol. FASDs encompass a range of physical and neurodevelopmental problems that can result from prenatal alcohol exposure. Some accept only FAS as a diagnosis, seeing the evidence as inconclusive with respect to other types.
Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis
Enjoying a drink while thinking about the baby in your tummy? Watch out! Picture 1 — Fetal Alcohol Syndrome Source — abuseaddiction. Fetal Alcohol Syndrome or Foetal Alcohol Syndrome is one of the most dreaded effects of drinking alcohol. It is a health condition commonly found in developed countries. When women drink alcohol during their pregnancy, it not only affects their own health.
Fetal alcohol spectrum disorder
Fetal Alcohol Spectrum Disorders FASD is a collection of developmental disorders affecting offspring that result from a woman drinking alcohol while she is pregnant. These disorders range from mild learning disabilities, to memory and attention deficits, to birth defects, to developmental delays, to serious behavior disorders, to sudden infant death syndrome. To prevent these birth defects, the answer is simple. A woman should not drink alcohol while she is pregnant or even if she might become pregnant because….
Use three-dimensional 3D facial laser scanned images from children with fetal alcohol syndrome FAS and controls to develop an automated diagnosis technique that can reliably and accurately identify individuals prenatally exposed to alcohol. A detailed dysmorphology evaluation, history of prenatal alcohol exposure, and 3D facial laser scans were obtained from individuals 86 FAS; 63 Control recruited from two study sites Cape Town, South Africa and Helsinki, Finland. Computer graphics, machine learning, and pattern recognition techniques were used to automatically identify a set of facial features that best discriminated individuals with FAS from controls in each sample. An automated feature detection and analysis technique was developed and applied to the two study populations. A unique set of facial regions and features were identified for each population that accurately discriminated FAS and control faces without any human intervention.