Attention deficit hyperactivity disorder (ADHD) is a heterogenous disorder that has a
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …

Objective: Machine learning (ML) has been applied to develop magnetic resonance imaging
(MRI)-based diagnostic classifiers for attention-deficit/hyperactivity disorder (ADHD). This …

This paper explores the current machine learning based methods used to identify Attention
Deficit Hyperactivity Disorder (ADHD) and depression in humans. Prevalence of mental …

This paper explores the current machine learning based methods used to identify Attention
Deficit Hyperactivity Disorder (ADHD) in humans. With ADHD being one of the most …

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is
increasing every year worldwide, is very important for early diagnosis and treatment …

This work focuses on the efficiency of the knowledge distillation approach in generating a
lightweight yet powerful BERT-based model for natural language processing (NLP) …

Artificial vision has made a great advance in the recognition of visual patterns that are not
perceptible by humans or that are biased in their interpretation. Among its applications …

El Trastorno por Déficit de Atención e Hiperactividad (TDAH), representa una preocupación
significativa en Estados Unidos y México, ya que afecta el rendimiento académico y la …

Attention-deficit/hyperactivity disorder (ADHD) is a neurological disorder characterized by
difficulties in controlling movement, impulsivity, and maintaining attention. Furthermore, it is …

The identification of ADHD is laden with a great number of challenges and obstacles. If a
patient is incorrectly diagnosed, there is a possibility that this will have adverse impact on …