Automated detection of ADHD: Current trends and future perspective
Attention deficit hyperactivity disorder (ADHD) is a heterogenous disorder that has a
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …
detrimental impact on the neurodevelopment of the brain. ADHD patients exhibit …
Machine learning and MRI-based diagnostic models for ADHD: are we there yet?
Objective: Machine learning (ML) has been applied to develop magnetic resonance imaging
(MRI)-based diagnostic classifiers for attention-deficit/hyperactivity disorder (ADHD). This …
(MRI)-based diagnostic classifiers for attention-deficit/hyperactivity disorder (ADHD). This …
Machine Learning in ADHD and Depression Mental Health Diagnosis: A Survey
C Nash, R Nair, SM Naqvi - IEEE Access, 2023 - ieeexplore.ieee.org
This paper explores the current machine learning based methods used to identify Attention
Deficit Hyperactivity Disorder (ADHD) and depression in humans. Prevalence of mental …
Deficit Hyperactivity Disorder (ADHD) and depression in humans. Prevalence of mental …
Machine learning and adhd mental health detection-a short survey
C Nash, R Nair, SM Naqvi - 2022 25th International Conference …, 2022 - ieeexplore.ieee.org
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 …
Deficit Hyperactivity Disorder (ADHD) in humans. With ADHD being one of the most …
Deep-learning-based ADHD classification using children's skeleton data acquired through the ADHD screening game
The identification of attention deficit hyperactivity disorder (ADHD) in children, which is
increasing every year worldwide, is very important for early diagnosis and treatment …
increasing every year worldwide, is very important for early diagnosis and treatment …
Larger models yield better results? Streamlined severity classification of ADHD-related concerns using BERT-based knowledge distillation
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) …
lightweight yet powerful BERT-based model for natural language processing (NLP) …
Design of a Collaborative Knowledge Framework for Personalised Attention Deficit Hyperactivity Disorder (ADHD) Treatments
P Chatpreecha, S Usanavasin - Children, 2023 - mdpi.com
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder. From the
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
data collected by the Ministry of Public Health, Thailand, it has been reported that more than …
Artificial vision algorithm for behavior recognition in children with ADHD in a smart home environment
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 …
perceptible by humans or that are biased in their interpretation. Among its applications …
ADHD Diagnosis Using Text Features and Predictive Machine Learning and Deep Learning Algorithms
Attention-deficit/hyperactivity disorder (ADHD) is a neurological disorder characterized by
difficulties in controlling movement, impulsivity, and maintaining attention. Furthermore, it is …
difficulties in controlling movement, impulsivity, and maintaining attention. Furthermore, it is …
Cognitive Based Attention Deficit Hyperactivity Disorder Detection with Ability Assessment Using Auto Encoder Based Hidden Markov Model
Attention deficit hyperactivity disorder (ADHD) is a frequent Neurogenerative mental
disorder. It can persist in adulthood and be expressed as a cognitive complaint. Behavioural …
disorder. It can persist in adulthood and be expressed as a cognitive complaint. Behavioural …