PhD student, F.R.S.-FNRS, University of Mons
Data Mining for ADHD & ASD prediction based on resting-state fMRI signals: A literature review
Despite ongoing research advances, mental disorders remain subject to the absence of a common etiology. Biomarker research is of paramount importance in this respect. In children, an improved knowledge of Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) would allow to diagnose these disorders better and earlier. Our presentation aims to give a synthesis of the data mining research for ADHD & ASD diagnosis based on rs-fMRI signals.
Sarah Itani obtained the computer science engineering degree from the Faculty of Engineering of the University of Mons (UMONS), Belgium, in 2016. She is currently a research fellow of the Belgian National Science Foundation (F.R.S.-FNRS) at the University of Mons. Her Ph.D. thesis is focused on medical diagnosis aid, through machine learning and artificial intelligence.