Autism

Deep-Learning-Based Analysis Reveals a Social Behavior Deficit in Mice Exposed Prenatally to Nicotine.

Cigarette smoking during pregnancy is known to be associated with the incidence of attention-deficit/hyperactive disorder (ADHD). Recent developments in deep learning algorithms enable us to assess the behavioral phenotypes of animal models without cognitive bias during manual analysis. In this study, we established prenatal nicotine exposure (PNE) mice and evaluated their behavioral phenotypes us...

M2AI-CVD: Multi-modal AI approach cardiovascular risk prediction system using fundus images.

Cardiovascular diseases (CVD) represent a significant global health challenge, often remaining undetected until severe cardiac events, such as heart attacks or strokes, occur. In regions like Qatar, research focused on non-invasive CVD identification methods, such as retinal imaging and dual-energy X-ray absorptiometry (DXA), is limited. This study presents a groundbreaking system known as Multi-M...

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning.

Identification of isocitrate dehydrogenase (IDH)-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment plann...

[Development of prognostic clinical and genetic models of the risk of low bone mineral density using neural network training].

BACKGROUND: Osteoporosis is a common age-related disease with disabling consequences, the early diagnosis of which is difficult due to its long and hi...

Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into nov...

ASD-GResTM: Deep Learning Framework for ASD classification using Gramian Angular Field.

Autism Spectrum Disorder (ASD) is a heterogeneous disorder in children, and the current clinical diagnosis is accomplished using behavioral, cognitive...

Effectiveness of Robotic Intervention on Improving Social Development and Participation of Children with Autism Spectrum Disorder - A Randomised Controlled Trial.

Evidence-based robotic intervention programmes for children with autism spectrum disorder (ASD) have been limited. As yet, there is insufficient evide...

Deep learning algorithm for fully automated measurement of sagittal balance in adult spinal deformity.

AIM: Deep learning (DL) algorithms can be used for automated analysis of medical imaging. The aim of this study was to assess the accuracy of an innov...

Pattern recognition in the nucleation kinetics of non-equilibrium self-assembly.

Inspired by biology's most sophisticated computer, the brain, neural networks constitute a profound reformulation of computational principles. Analogo...

Classification of clinically actionable genetic mutations in cancer patients.

Personalized medicine in cancer treatment aims to treat each individual's cancer tumor uniquely based on the genetic sequence of the cancer patient an...

Exploring White Matter Abnormalities in Young Children with Autism Spectrum Disorder: Integrating Multi-shell Diffusion Data and Machine Learning Analysis.

RATIONALE AND OBJECTIVES: This study employed tract-based spatial statistics (TBSS) to investigate abnormalities in the white matter microstructure am...

Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism.

The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. T...

Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer.

Colorectal cancer (CRC) is a primary global health concern, and identifying the molecular pathways, genetic subtypes, and mutations associated with CR...

Estimation of potential wildfire behavior characteristics to assess wildfire danger in southwest China using deep learning schemes.

Accurate estimation of potential wildfire behavior characteristics (PWBC) can improve wildfire danger assessment. However, wildfire behavior has been ...

Brain organoids and organoid intelligence from ethical, legal, and social points of view.

Human brain organoids, aka cerebral organoids or earlier "mini-brains", are 3D cellular models that recapitulate aspects of the developing human brain...

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol.

More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memor...

Applying data science methodologies with artificial intelligence variant reinterpretation to map and estimate genetic disorder prevalence utilizing clinical data.

Data science methodologies can be utilized to ascertain and analyze clinical genetic data that is often unstructured and rarely used outside of patien...

Classification of attention deficit hyperactivity disorder using machine learning on an EEG dataset.

The neurodevelopmental disorder, Attention Deficit Hyperactivity Disorder (ADHD), frequently affecting youngsters, is characterized by persistent patt...

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures.

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing ...

Modified Meta Heuristic BAT with ML Classifiers for Detection of Autism Spectrum Disorder.

ASD (autism spectrum disorder) is a complex developmental and neurological disorder that impacts the social life of the affected person by disturbing ...