TY - JOUR
T1 - How many tests do you need to diagnose Learning Disabilities?
AU - Vezzoli, Yvonne
AU - Folgieri, Raffaella
AU - Vanutelli, Maria Elide
AU - Lucchiari, Claudio
PY - 2018
Y1 - 2018
N2 - The diagnosis of Learning Disabilities (LD) is frequently subject to cognitive biases. In Italy, minimal diagnostic standards have been identified during a national Consensus Conference (2010). However, specialists use different protocols to assess reading and cognitive abilities. Thus, we propose to support LDs diagnosis with Artificial Neural Networks (ANN). Clinical results from 203 reports were input to investigate which ones can predict LD diagnosis. In addition, correlations among LDs were explored. Preliminary results show that ANNs can be useful to support a clinical diagnosis of LDs with an 81.93% average accuracy, and, under certain conditions, with a 99% certainty. Additionally, the 10 most meaningful tests for each LD have been identified and significant correlations between dyscalculia and dyslexia were found.
AB - The diagnosis of Learning Disabilities (LD) is frequently subject to cognitive biases. In Italy, minimal diagnostic standards have been identified during a national Consensus Conference (2010). However, specialists use different protocols to assess reading and cognitive abilities. Thus, we propose to support LDs diagnosis with Artificial Neural Networks (ANN). Clinical results from 203 reports were input to investigate which ones can predict LD diagnosis. In addition, correlations among LDs were explored. Preliminary results show that ANNs can be useful to support a clinical diagnosis of LDs with an 81.93% average accuracy, and, under certain conditions, with a 99% certainty. Additionally, the 10 most meaningful tests for each LD have been identified and significant correlations between dyscalculia and dyslexia were found.
KW - Artificial neural networks
KW - Dyslexia
KW - Learning disabilities
KW - Artificial neural networks
KW - Dyslexia
KW - Learning disabilities
UR - http://hdl.handle.net/10807/131729
UR - http://www.ledonline.it/neuropsychologicaltrends
U2 - 10.7358/neur-2018-023-lucc
DO - 10.7358/neur-2018-023-lucc
M3 - Article
SN - 1970-321X
VL - 2018
SP - 67
EP - 81
JO - Neuropsychological Trends
JF - Neuropsychological Trends
ER -