DeEN: Deep Ensemble Framework for Neuroatypicality Classification

This paper proposes a Machine Learning (ML) based ensemble framework to identify neuroatypicality among individuals. The focus of this study is neuroatypicality, which refers to individuals who suffer from irregular neurological functioning. The neuroatypicality conditions includes ASD, ADHD and Dyslexia. The neuroatypical individuals face challenges in emotional regulation, educational intervention, decision-making, and problem-solving. Diagnosis of neuroatypicality is a difficult task due to the varied symptoms among individuals. Brain signal analysis is one of the common parameters to identify neuroatypicality. This paper focuses on brain signal based ML framework to classify the typically and neuroatypically developed individuals. The contribution of this paper is to propose an ensemble framework for early diagnosis of neuro disorder which forms a basis to enable Artificial Intelligence (AI) to generate heuristics for further academic and medical research.