Pediatrics

ADHD/ADD

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

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Semi-supervised Learning for the BioNLP Gene Regulation Network.

BACKGROUND: The BioNLP Gene Regulation Task has attracted a diverse collection of submissions showca...

Installing a Local Copy of the Reactome Web Site and Knowledgebase.

The Reactome project builds, maintains, and publishes a knowledgebase of biological pathways. The in...

FoodWiki: Ontology-Driven Mobile Safe Food Consumption System.

An ontology-driven safe food consumption mobile system is considered. Over 3,000 compounds are being...

Identifying the Basal Ganglia network model markers for medication-induced impulsivity in Parkinson's disease patients.

Impulsivity, i.e. irresistibility in the execution of actions, may be prominent in Parkinson's disea...

Transversus abdominis plane (TAP) block after robot-assisted laparoscopic hysterectomy: a randomised clinical trial.

BACKGROUND: Transversus abdominis plane (TAP) block is widely used as a part of pain management afte...

Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate res...

Monitoring Neuro-Motor Recovery From Stroke With High-Resolution EEG, Robotics and Virtual Reality: A Proof of Concept.

A novel system for the neuro-motor rehabilitation of upper limbs was validated in three sub-acute po...

Competition and Collaboration in Cooperative Coevolution of Elman Recurrent Neural Networks for Time-Series Prediction.

Collaboration enables weak species to survive in an environment where different species compete for ...

Urodynamic Efficacy and Safety of Mirabegron Add-on Treatment with Tamsulosin for Japanese Male Patients with Overactive Bladder.

OBJECTIVES: To investigate urodynamic efficacy and safety of mirabegron add-on treatment with tamsul...

A Machine Learning Approach to Explain Drug Selectivity to Soluble and Membrane Protein Targets.

Improved understanding of the forces that determine drug specificity to their targets is important f...

Exploring the dynamics of design fluency in children with and without ADHD using artificial neural networks.

The neuropsychology of attention deficit/hyperactivity disorder (ADHD) has been extensively studied,...

Predictors of schizophrenia spectrum disorders in early-onset first episodes of psychosis: a support vector machine model.

Identifying early-onset schizophrenia spectrum disorders (SSD) at a very early stage remains challen...

Genetic Risk Scores in Stroke Research and Care.

Stroke remains a leading cause of death and disability worldwide. While well-established risk factor...

The Chest X- Ray: The Ship has Sailed, But Has It?

In the past, the chest X-ray (CXR) was a traditional age and amount requirement used to assess poten...

Micro-ring resonator assisted spiking neural network for efficient object detection.

Optical computing and spiking neural networks (SNNs) have garnered significant attention as next-gen...

Clinicians must participate in the development of multimodal AI.

Multimodal artificial intelligence (AI) is a powerful new technological advance, capable of simultan...

The radiologist and data: Do we add value or is data just data?

Artificial intelligence in radiology critically depends on vast amounts of quality data, and there a...

Transforming 3D MRI to 2D Feature Maps Using Pre-Trained Models for Diagnosis of Attention Deficit Hyperactivity Disorder.

According to the World Health Organization (WHO), approximately 5% of children and 2.5% of adults s...

An MRI-based deep transfer learning radiomics nomogram for predicting meningioma grade.

The aim of this study was to establish a nomogram based on clinical, radiomics, and deep transfer le...

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