Autism

Use of the PARO robot as a social mediator in a sample of children with neurodevelopmental disorders and typical development.

BACKGROUND: Social robotics is a research field aimed at providing robots with skills related to social behavior and natural human interaction. Many studies have demonstrated the efficacy of these robots as socio-communicative mediators. Others have used them to create a new communication channel and promote social interaction in chil-dren with autism spectrum disorder (ASD). For children with ASD...

Prediction of Cancer Treatment Using Advancements in Machine Learning.

Many cancer patients die due to their treatment failing because of their disease's resistance to chemotherapy and other forms of radiation therapy. Resistance may develop at any stage of therapy, even at the beginning. Several factors influence current therapy, including the type of cancer and the existence of genetic abnormalities. The response to treatment is not always predicted by the existenc...

Network Biology and Medicine to Rescue: Applications for Retinal Disease Mechanisms and Therapy.

Inherited retinal degenerations (IRDs) are clinically and genetically heterogenous blinding diseases that manifest through dysfunction of target cells...

Graph-Based Disease Prediction in Neuroimaging: Investigating the Impact of Feature Selection.

In biomedical machine learning, data often appear in the form of graphs. Biological systems such as protein interactions and ecological or brain netwo...

DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

MOTIVATION: Understanding the functional consequence of genetic variants, especially the non-coding ones, is important but particularly challenging. G...

Optimization scheme of machine learning model for genetic division between northern Han, southern Han, Korean and Japanese.

Han Chinese, Korean and Japanese are the main populations of East Asia, and Han Chinese presents a gradient admixture from north to south. There are d...

The genetic algorithm-aided three-stage ensemble learning method identified a robust survival risk score in patients with glioma.

Ensemble learning is a kind of machine learning method which can integrate multiple basic learners together and achieve higher accuracy. Recently, sin...

Distributed nonsynchronous event-triggered state estimation of genetic regulatory networks with hidden Markovian jumping parameters.

In this paper, the distributed state estimation problem of genetic regulatory networks (GRNs) with hidden Markovian jumping parameters (HMJPs) is expl...

Braitenberg Vehicles as Developmental Neurosimulation.

Connecting brain and behavior is a longstanding issue in the areas of behavioral science, artificial intelligence, and neurobiology. As is standard am...

KLFDAPC: a supervised machine learning approach for spatial genetic structure analysis.

Geographic patterns of human genetic variation provide important insights into human evolution and disease. A commonly used tool to detect and describ...

Novel Insights Into Facial Emotion Encoding in Autism Spectrum Disorder Through Deep Learning.

Development of an Interactive Total Body Robot Enhanced Imitation Therapy for ASD children.

Autism is a neurodevelopmental disorder in which the available therapies target the improvement of social skills, in order to ensure a high quality of...

Three Study Cases of Social Robotics in Autism Spectrum Disorder Treatment: Personalization and Usability of CASTOR Robot.

Social assistive robotics in autism has been implemented in studies and therapies to improve social skills and encourage children to comply with thera...

Sharing Worlds: Design of a Real-Time Attention Classifier for Robotic Therapy of ASD Children.

Joint attention is the capacity of sharing attention between two agents and an aspect of the environment, through the use of different cues, namely ga...

Improving the noninvasive classification of glioma genetic subtype with deep learning and diffusion-weighted imaging.

BACKGROUND: Diagnostic classification of diffuse gliomas now requires an assessment of molecular features, often including IDH-mutation and 1p19q-code...

Extreme learning machine and genetic algorithm in quantitative analysis of sulfur hexafluoride by infrared spectroscopy.

Owing to the general disadvantages of traditional neural networks in gas concentration inversion, such as slow training speed, sensitive learning rate...

Deep learning-based identification of genetic variants: application to Alzheimer's disease classification.

Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in ...

A deep learning framework for characterization of genotype data.

Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality redu...

Neural network-based integration of polygenic and clinical information: development and validation of a prediction model for 10-year risk of major adverse cardiac events in the UK Biobank cohort.

BACKGROUND: In primary cardiovascular disease prevention, early identification of high-risk individuals is crucial. Genetic information allows for the...

Clinical Applications of Artificial Intelligence in Positron Emission Tomography of Lung Cancer.

The ability of a computer to perform tasks normally requiring human intelligence or artificial intelligence (AI) is not new. However, until recently, ...