ADHD/ADD

Broad-Spectrum Profiling of Drug Safety via Learning Complex Network.

Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, a reproducible method to assess drug safety systematically and quantitatively is still missing. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug-gene-adverse drug reaction (AD...

Twitter Analysis of the Nonmedical Use and Side Effects of Methylphenidate: Machine Learning Study.

BACKGROUND: Methylphenidate, a stimulant used to treat attention deficit hyperactivity disorder, has the potential to be used nonmedically, such as for studying and recreation. In an era when many people actively use social networking services, experience with the nonmedical use or side effects of methylphenidate might be shared on Twitter.

Natural language processing of clinical mental health notes may add predictive value to existing suicide risk models.

BACKGROUND: This study evaluated whether natural language processing (NLP) of psychotherapy note text provides additional accuracy over and above curr...

On the localness modeling for the self-attention based end-to-end speech synthesis.

Attention based end-to-end speech synthesis achieves better performance in both prosody and quality compared to the conventional "front-end"-"back-end...

Rolling Locomotion of Cable-Driven Soft Spherical Tensegrity Robots.

Soft spherical tensegrity robots are novel steerable mobile robotic platforms that are compliant, lightweight, and robust. The geometry of these robot...

DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI.

BACKGROUND: Resting state fMRI has emerged as a popular neuroimaging method for automated recognition and classification of brain disorders. Attention...

Assessing Risk Among Correctional Community Probation Populations: Predicting Reoffense With Mobile Neurocognitive Assessment Software.

We seek to address current limitations of forensic risk assessments by introducing the first mobile, self-scoring, risk assessment software that relie...

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and specialists over an extensive period of time. Communic...

ADHD classification by dual subspace learning using resting-state functional connectivity.

As one of the most common neurobehavioral diseases in school-age children, Attention Deficit Hyperactivity Disorder (ADHD) has been increasingly studi...

How will digitalisation affect patient treatment in arthroplasty? Part I: Intraoperative aspects.

We cannot deny that technology has become an important part of our daily life, not only in automobiles, houses or cellphones but also in hospitals. In...

Characterization of the complete chloroplast genome of (Cupressaceae), an herb to treat lumbar tuberculosis in China.

belongs to the family Cupressaceae that the branches and leaves is an important Traditional Chinese Medicine in China. In this article, the complete ...

Computer-Aided Diagnosis Systems in Diagnosing Malignant Thyroid Nodules on Ultrasonography: A Systematic Review and Meta-Analysis.

BACKGROUND: Computer-aided diagnosis (CAD) systems are being applied to the ultrasonographic diagnosis of malignant thyroid nodules, but it remains co...

Characterization and antifungal activity of the yellow pigment produced by a sp. DBS4 isolated from the lichen .

This study emphasis the production of yellow pigment from endolichenic sp. isolated from the lichen (Afzel. ex Ach.) B.J. Moore Yellow pigment-produ...

Use of deep learning to detect personalized spatial-frequency abnormalities in EEGs of children with ADHD.

OBJECTIVE: Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent neurobehavioral disorders. Studies have tried to find the neur...

Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death.

BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic information beyond structured (coded) information. For majo...

Establishing phone-pair co-usage by comparing mobility patterns.

In forensic investigations it is often of value to establish whether two phones were used by the same person during a given time period. We present a ...

Learning Cascade Attention for fine-grained image classification.

Fine-grained image classification is a challenging task due to the large inter-class difference and small intra-class difference. In this paper, we pr...

Intelligent architectures for robotics: The merging of cognition and emotion.

What is the place of emotion in intelligent robots? In the past two decades, researchers have advocated for the inclusion of some emotion-related comp...

Predicting likelihood of psychological disorders in PlayerUnknown's Battlegrounds (PUBG) players from Asian countries using supervised machine learning.

Multiplayer Online Battle Arena (MOBA) has become one of the most popular genre of online video games played by gamers worldwide. Previous studies hav...

A non-linear mathematical model using optical sensor to predict heart decellularization efficacy.

One of the main problems of the decellularization technique is the subjectivity of the final evaluation of its efficacy in individual organs. This pro...