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ADHD/ADD

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

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Road crack segmentation using an attention residual U-Net with generative adversarial learning.

This paper proposed an end-to-end road crack segmentation model based on attention mechanism and dee...

Learning Cellular Phenotypes through Supervision.

Image-based cell phenotyping is an important and open problem in computational pathology. The two pr...

A 3D multiscale view convolutional neural network with attention for mental disease diagnosis on MRI images.

Computer Assisted Diagnosis (CAD) based on brain Magnetic Resonance Imaging (MRI) is a popular resea...

Which methods are the most effective in enabling novice users to participate in ontology creation? A usability study.

Producing findable, accessible, interoperable and reusable (FAIR) data cannot be accomplished solely...

Hybrid Predictive Ensembles: Synergies Between Human and Computational Forecasts.

An increasing proportion of decisions, design choices, and predictions are being made by hybrid grou...

AI-Driven Growth of DSOs.

DSOs have been at the forefront of adopting technology that demonstrates value-add to their business...

UniProt: the universal protein knowledgebase in 2021.

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and free...

Reproducible Evaluation of Diffusion MRI Features for Automatic Classification of Patients with Alzheimer's Disease.

Diffusion MRI is the modality of choice to study alterations of white matter. In past years, various...

Predicting single-cell gene expression profiles of imaging flow cytometry data with machine learning.

High-content imaging and single-cell genomics are two of the most prominent high-throughput technolo...

Regularized Bagged Canonical Component Analysis for Multiclass Learning in Brain Imaging.

A fundamental problem of supervised learning algorithms for brain imaging applications is that the n...

Machine Learning for Work Disability Prevention: Introduction to the Special Series.

Rapid development in computer technology has led to sophisticated methods of analyzing large dataset...

Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a ...

Autonomous Control of a Tendon-driven Robotic Limb with Elastic Elements Reveals that Added Elasticity can Enhance Learning.

Passive elastic elements can contribute to stability, energetic efficiency, and impact absorption in...

Can machine-learning methods really help predict suicide?

PURPOSE OF REVIEW: In recent years there has been interest in the use of machine learning in suicide...

Lateral Oscillation and Body Compliance Help Snakes and Snake Robots Stably Traverse Large, Smooth Obstacles.

Snakes can move through almost any terrain. Similarly, snake robots hold the promise as a versatile ...

Advancing PICO element detection in biomedical text via deep neural networks.

MOTIVATION: In evidence-based medicine, defining a clinical question in terms of the specific patien...

The Parasitic Nature of Social AI: Sharing Minds with the Mindless.

Can artificial intelligence (AI) develop the potential to be our partner, and will we be as sensitiv...

The neXtProt knowledgebase in 2020: data, tools and usability improvements.

The neXtProt knowledgebase (https://www.nextprot.org) is an integrative resource providing both data...

Efficacy of an Automated Robotic Cleaning Device for Compounding Pharmacies.

Compounded medicinal products should be prepared using an appropriate quality-assurance system. Clea...

Classification of Alzheimer's Disease with Respect to Physiological Aging with Innovative EEG Biomarkers in a Machine Learning Implementation.

BACKGROUND: Several studies investigated clinical and instrumental differences to make diagnosis of ...

A guide to machine learning for bacterial host attribution using genome sequence data.

With the ever-expanding number of available sequences from bacterial genomes, and the expectation th...

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