Autism

Population Graph-Based Multi-Model Ensemble Method for Diagnosing Autism Spectrum Disorder.

With the advancement of brain imaging techniques and a variety of machine learning methods, significant progress has been made in brain disorder diagnosis, in particular Autism Spectrum Disorder. The development of machine learning models that can differentiate between healthy subjects and patients is of great importance. Recently, graph neural networks have found increasing application in domains...

Path Planning of Mobile Robots Based on a Multi-Population Migration Genetic Algorithm.

In the field of robot path planning, aiming at the problems of the standard genetic algorithm, such as premature maturity, low convergence path quality, poor population diversity, and difficulty in breaking the local optimal solution, this paper proposes a multi-population migration genetic algorithm. The multi-population migration genetic algorithm randomly divides a large population into several...

Ordered interpersonal synchronisation in ASD children via robots.

Children with autistic spectrum disorders (ASD) experience persistent disrupted coordination in interpersonal synchronisation that is thought to be as...

Towards Automated Emotion Classification of Atypically and Typically Developing Infants.

The World Health Organization estimates that 15 million infants are born preterm every year [1]. This is of concern because these infants have a signi...

Evaluation of a genetic risk score for severity of COVID-19 using human chromosomal-scale length variation.

INTRODUCTION: The course of COVID-19 varies from asymptomatic to severe in patients. The basis for this range in symptoms is unknown. One possibility ...

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.

The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and enteric nervous system (ENS). Clinical and experimen...

Application of BERT to Enable Gene Classification Based on Clinical Evidence.

The identification of profiled cancer-related genes plays an essential role in cancer diagnosis and treatment. Based on literature research, the class...

Deep neural network improves the estimation of polygenic risk scores for breast cancer.

Polygenic risk scores (PRS) estimate the genetic risk of an individual for a complex disease based on many genetic variants across the whole genome. I...

The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.

Automated semantic segmentation of multiple knee joint tissues is desirable to allow faster and more reliable analysis of large datasets and to enable...

The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.

OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavio...

Genome-wide association study-based deep learning for survival prediction.

Informative and accurate survival prediction with individualized dynamic risk profiles over time is critical for personalized disease prevention and c...

Identification of risk features for complication in Gaucher's disease patients: a machine learning analysis of the Spanish registry of Gaucher disease.

BACKGROUND: Since enzyme replacement therapy for Gaucher disease (MIM#230800) has become available, both awareness of and the natural history of the d...

A multi-task, multi-stage deep transfer learning model for early prediction of neurodevelopment in very preterm infants.

Survivors following very premature birth (i.e., ≤ 32 weeks gestational age) remain at high risk for neurodevelopmental impairments. Recent advances in...

Optimal robot for intervention for individuals with autism spectrum disorders.

With recent rapid advances in technology, human-like robots have begun functioning in a variety of ways. As increasing anecdotal evidence suggests, ro...

MRI-visible dilated perivascular spaces in healthy young adults: A twin heritability study.

We investigated the narrow-sense heritability of MRI-visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138...

Exploring gene-gene interaction in family-based data with an unsupervised machine learning method: EPISFA.

Gene-gene interaction (G × G) is thought to fill the gap between the estimated heritability of complex diseases and the limited genetic proportion exp...

DeepVariant-on-Spark: Small-Scale Genome Analysis Using a Cloud-Based Computing Framework.

Although sequencing a human genome has become affordable, identifying genetic variants from whole-genome sequence data is still a hurdle for researche...

Precision psychiatry in clinical practice.

The treatment of depression represents a major challenge for healthcare systems and choosing among the many available drugs without objective guidance...

Case of slowly progressive type 1 diabetes mellitus with drastically reduced insulin secretory capacity after immune checkpoint inhibitor treatment for advanced renal cell carcinoma.

We encountered a 55-year-old Japanese man with advanced renal cell carcinoma and slowly progressive type 1 diabetes mellitus (SPT1DM), whose insulin s...

The DREAM Dataset: Supporting a data-driven study of autism spectrum disorder and robot enhanced therapy.

We present a dataset of behavioral data recorded from 61 children diagnosed with Autism Spectrum Disorder (ASD). The data was collected during a large...