PUPILLONET: SUPPORT VECTOR MACHINE FOR GENETIC DISEASES DETECTION IN PAEDIATRIC AGE
Keywords:
Chromatic Pupillometry, Machine learning, SVM, CDSS.Abstract
Inherited retinal diseases cause severe visual deficits in children. They are classified in outer and inner retina diseases, and often cause blindness in childhood. The diagnosis for this type of illness is challenging, given the wide range of clinical and genetic causes (with over 200 causative genes). It is routinely based on a complex pattern of clinical tests, including invasive ones, not always appropriate for infants or young children. A different approach is thus needed, that exploits Chromatic Pupillometry, a technique increasingly used to assess outer and inner retina functions. Using a specific medical device (pupillometer) and a proprietary machine learning decision support system, a hybrid solution is suggested. Features collected from pupillometric data are classified by means of SVM in paediatric patients has been diagnosed using the CDSS.
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