Identifying and Reporting Child abuse

Gell-Mann-Low Criticality in Neural Networks.

Criticality is deeply related to optimal computational capacity. The lack of a renormalized theory of critical brain dynamics, however, so far limits insights into this form of biological information processing to mean-field results. These methods neglect a key feature of critical systems: the interaction between degrees of freedom across all length scales, required for complex nonlinear computati...

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 risk ADHD-associated variants and genes with significant P-values, they may neglect the combined effect of multiple variants with insignificant P-values. Here, we proposed a convolutional neural network (CNN) to classify 1033 individuals diagnosed wi...

Addressing data imbalance problems in ligand-binding site prediction using a variational autoencoder and a convolutional neural network.

Since 2015, a fast growing number of deep learning-based methods have been proposed for protein-ligand binding site prediction and many have achieved ...

Enriching contextualized language model from knowledge graph for biomedical information extraction.

Biomedical information extraction (BioIE) is an important task. The aim is to analyze biomedical texts and extract structured information such as name...

The effects of robot-assisted left-hand training on hemispatial neglect in older patients with chronic stroke: A pilot and randomized controlled trial.

BACKGROUND: Even though a variety of rehabilitative technique have been implemented to ameliorate neglect symptoms of patients with stoke, the effects...

On the critical review of five machine learning-based algorithms for predicting protein stability changes upon mutation.

A review, recently published in this journal by Fang (2019), showed that methods trained for the prediction of protein stability changes upon mutation...

Integrating distal and proximal information to predict gene expression via a densely connected convolutional neural network.

MOTIVATION: Interactions among cis-regulatory elements such as enhancers and promoters are main driving forces shaping context-specific chromatin stru...

Fused Group Lasso Regularized Multi-Task Feature Learning and Its Application to the Cognitive Performance Prediction of Alzheimer's Disease.

Alzheimer's disease (AD) is characterized by gradual neurodegeneration and loss of brain function, especially for memory during early stages. Regressi...

Breast mass detection and diagnosis using fused features with density.

BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis tec...

SmartSock: a wearable platform for context-aware assessment of ankle edema.

Ankle edema an important symptom for monitoring patients with chronic systematic diseases. It is an important indicator of onset or exacerbation of a ...

Gist Representations and Communication of Risks about HIV-AIDS: A Fuzzy-Trace Theory Approach.

As predicted by fuzzy-trace theory, people with a range of training—from untrained adolescents to expert physicians—are susceptible to biases and erro...