ADHD/ADD

Addressing ergonomic, skill acquisition and mentoring constraints that may be contributory to gender disparity in surgery: a 'value add' for robotics?

TF-Unet:An automatic cardiac MRI image segmentation method.

Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have been used to guide clinical ablation of different types of arrhythmias in recent years. MRI images are now mostly used for model building. In cardiac modeling studies, the degree of segmentation of the heart image determines the success of subsequent 3D reconstructions. Therefore, a fully automated se...

Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.

Single-cell RNA sequencing (scRNA-seq) permits researchers to study the complex mechanisms of cell heterogeneity and diversity. Unsupervised clusterin...

Food Metabolomics.

Foods contain not only nutrients but also a wide variety of components related to flavor and functionality. Many studies have been conducted on the co...

[Protein modeling and design based on deep learning].

The accumulation of protein sequence and structure data allows researchers to obtain large amount of descriptive information, simultaneously it poses ...

The difficult role of Artificial Intelligence in Medical Liability: to err is not only human.

The entrance of Artificial Intelligence (AI) as a new actor in the doctor-patient relationship has encouraged important legal and ethi-cal considerati...

Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5.

Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the ...

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 deep FCN with generative adversarial learning. We cre...

Learning Cellular Phenotypes through Supervision.

Image-based cell phenotyping is an important and open problem in computational pathology. The two principal challenges are: 1) making the cell cluster...

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 research field for the computer science and medical eng...

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 by data curators in all disciplines. In biology, ...

Hybrid Predictive Ensembles: Synergies Between Human and Computational Forecasts.

An increasing proportion of decisions, design choices, and predictions are being made by hybrid groups consisting of humans and artificial intelligenc...

AI-Driven Growth of DSOs.

DSOs have been at the forefront of adopting technology that demonstrates value-add to their businesses. Hence, DSOs have been quick to identify artifi...

UniProt: the universal protein knowledgebase in 2021.

The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated w...

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 works have used diffusion MRI for automatic class...

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 technologies for studying cellular properties and function...

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 number of features far exceeds the number of subjec...

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 nationally representative sample. Participants wer...

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

Rapid development in computer technology has led to sophisticated methods of analyzing large datasets with the aim of improving human decision making....

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 platform to traverse complex environments such as ...