Pediatrics

ADHD/ADD

Latest AI and machine learning research in adhd/add for healthcare professionals.

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Showing 127-147 of 6,134 articles
Progressive Feature Fusion Attention Dense Network for Speckle Noise Removal in OCT Images.

Although deep learning for Big Data analytics has achieved promising results in the field of optical...

Deep Factor Learning for Accurate Brain Neuroimaging Data Analysis on Discrimination for Structural MRI and Functional MRI.

Analysis of neuroimaging data (e.g., Magnetic Resonance Imaging, structural and functional MRI) play...

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psy...

Adaptive self-supervised learning for sequential recommendation.

Sequential recommendation typically utilizes deep neural networks to mine rich information in intera...

The Use of fMRI Regional Analysis to Automatically Detect ADHD Through a 3D CNN-Based Approach.

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a ...

Achieving Occam's razor: Deep learning for optimal model reduction.

All fields of science depend on mathematical models. Occam's razor refers to the principle that good...

Prediction of Clonal Complexes from Multilocus Variable Number Tandem Repeat Analysis Patterns Using a Machine Learning Approach.

Multilocus variable number tandem repeat analysis (MLVA) is a molecular subtyping technique that rem...

A tree-based explainable AI model for early detection of Covid-19 using physiological data.

With the outbreak of COVID-19 in 2020, countries worldwide faced significant concerns and challenges...

Siamese Graph Convolutional Network quantifies increasing structure-function discrepancy over the cognitive decline continuum.

BACKGROUND AND OBJECTIVE: Alzheimer's disease dementia (ADD) is well known to induce alterations in ...

Implementation of Anxiety UK's Ask Anxia Chatbot Service: Lessons Learned.

Chatbots are increasingly being applied in the context of health care, providing access to services ...

A robust event-driven approach to always-on object recognition.

We propose a neuromimetic architecture capable of always-on pattern recognition, i.e. at any time du...

Attention-Like Multimodality Fusion With Data Augmentation for Diagnosis of Mental Disorders Using MRI.

The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and thera...

DTDO: Driving Training Development Optimization enabled deep learning approach for brain tumour classification using MRI.

A brain tumour is an abnormal mass of tissue. Brain tumours vary in size, from tiny to large. Moreov...

Cherry on Top or Real Need? A Review of Explainable Machine Learning in Kidney Transplantation.

Research on solid organ transplantation has taken advantage of the substantial acquisition of medica...

ADHD classification with cross-dataset feature selection for biomarker consistency detection.

Attention deficit hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in childr...

Machine learning based DNA melt curve profiling enables automated novel genotype detection.

Surveillance for genetic variation of microbial pathogens, both within and among species, plays an i...

Improved clinical data imputation via classical and quantum determinantal point processes.

Imputing data is a critical issue for machine learning practitioners, including in the life sciences...

Dynamic multilayer growth: Parallel vs. sequential approaches.

The decision of when to add a new hidden unit or layer is a fundamental challenge for constructive a...

3D-printed portable device for illicit drug identification based on smartphone-imaging and artificial neural networks.

In this manuscript, a 3D-printed analytical device has been successfully developed to classify illic...

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