Autism

Sparse deep dictionary learning identifies differences of time-varying functional connectivity in brain neuro-developmental study.

Recently, the focus of functional connectivity analysis of human brain has shifted from merely revealing the inter-regional functional correlation over the entire scan duration to capturing the time-varying information of brain networks and characterizing time-resolved reoccurring patterns of connectivity. Much effort has been invested into developing approaches that can track changes in re-occurr...

Detection of eye contact with deep neural networks is as accurate as human experts.

Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looking direction is a challenging task, but eye contact can be effectively captured by a wearable point-of-view camera which provides a unique viewpoint. ...

Self-channel-and-spatial-attention neural network for automated multi-organ segmentation on head and neck CT images.

Accurate segmentation of organs at risk (OARs) is necessary for adaptive head and neck (H&N) cancer treatment planning, but manual delineation is tedi...

How wide is the application of genetic big data in biomedicine.

In the era of big data, massive genetic data, as a new industry, has quickly swept almost all industries, especially the pharmaceutical industry. As c...

A machine learning toolkit for genetic engineering attribution to facilitate biosecurity.

The promise of biotechnology is tempered by its potential for accidental or deliberate misuse. Reliably identifying telltale signatures characteristic...

Feature replacement methods enable reliable home video analysis for machine learning detection of autism.

Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million children worldwide and for which early diagnosis is critical to the outc...

Training confounder-free deep learning models for medical applications.

The presence of confounding effects (or biases) is one of the most critical challenges in using deep learning to advance discovery in medical imaging ...

Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto-Encoder Feature Representation.

Autism spectrum disorder (ASD) is a developmental disorder with a life-span disability. While diagnostic instruments have been developed and qualified...

Identifying individuals with autism spectrum disorder based on the principal components of whole-brain phase synchrony.

Autism spectrum disorder (ASD) is a brain disorder that develops during an early stage of childhood. Previous neuroimaging-based diagnostic models for...

Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus an...

Robot dramas may improve joint attention of Chinese-speaking low-functioning children with autism: stepped wedge trials.

INTRODUCTION: Children with autism spectrum disorder (ASD), especially those with low cognitive functioning, have deficits in joint attention. Previou...

Integration of a Social Robot in a Pedagogical and Logopedic Intervention with Children: A Case Study.

The effectiveness of social robots such as NAO in pedagogical therapies presents a challenge. There is abundant literature focused on therapies using ...

An integrative knowledge graph for rare diseases, derived from the Genetic and Rare Diseases Information Center (GARD).

BACKGROUND: The Genetic and Rare Diseases (GARD) Information Center was established by the National Institutes of Health (NIH) to provide freely acces...

Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy.

BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but remain underdiagnosed. This feasibility project te...

Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features.

BACKGROUND: Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which are genetically complex and heterogeneous with mo...

A DNA-Based Intelligent Expert System for Personalised Skin-Health Recommendations.

Intensive attention on personalised skin-health solutions is on account of incomparable love of skin and an urgent need for effective treatment. In th...

Single Volume Image Generator and Deep Learning-Based ASD Classification.

Autism spectrum disorder (ASD) is an intricate neuropsychiatric brain disorder characterized by social deficits and repetitive behaviors. Deep learnin...

Artificial intelligence for the measurement of vocal stereotypy.

Both researchers and practitioners often rely on direct observation to measure and monitor behavior. When these behaviors are too complex or numerous ...

Scalable classification of organisms into a taxonomy using hierarchical supervised learners.

Accurately identifying organisms based on their partially available genetic material is an important task to explore the phylogenetic diversity in an ...

Automated identification of postural control for children with autism spectrum disorder using a machine learning approach.

It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this stu...