Autism

Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability.

The early detection of Alzheimer's Disease (AD) is thought to be important for effective intervention and management. Here, we explore deep learning methods for the early detection of AD. We consider both genetic risk factors and functional magnetic resonance imaging (fMRI) data. However, we found that the genetic factors do not notably enhance the AD prediction by imaging. Thus, we focus on build...

Genetic algorithm-based optimal design for fluidic artificial muscle (FAM) bundles.

In this paper, we present a design optimization framework for a fluidic artificial muscle (FAM) bundle subject to geometric constraints. The architecture of natural skeletal muscles allows for compact actuation packaging by distributing a substantial number of actuation elements or muscle fiber motor units, which are to be arranged, oriented, and sized in various formations. Many researchers have ...

A histopathology-based artificial intelligence system assisting the screening of genetic alteration in intrahepatic cholangiocarcinoma.

BACKGROUND: Targeted therapy for intrahepatic cholangiocarcinoma (ICC) shows superior survival outcomes but patients with certain targetable alteratio...

High-Speed Imaging-Based Particle Attribute Analysis of Spray-Dried Amorphous Solid Dispersions Using a Convolution Neural Network.

Spray drying is a well-established method for preparing amorphous solid dispersion (ASD) formulations to improve the oral bioavailability of poorly so...

Site-Invariant Meta-Modulation Learning for Multisite Autism Spectrum Disorders Diagnosis.

Large amounts of fMRI data are essential to building generalized predictive models for brain disease diagnosis. In order to conduct extensive data ana...

A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI.

In the current era, a lot of research is being done in the domain of disease diagnosis using machine learning. In recent times, one of the deadliest r...

Machine learning approaches and genetic determinants that influence the development of type 2 diabetes mellitus: a genetic association study in Brazilian patients.

This genetic association study including 120 patients with type 2 diabetes mellitus (T2DM) and 166 non-diabetic individuals aimed to investigate the a...

Inferring strain-level mutational drivers of phage-bacteria interaction phenotypes arising during coevolutionary dynamics.

The enormous diversity of bacteriophages and their bacterial hosts presents a significant challenge to predict which phages infect a focal set of bact...

Integrative analysis and knowledgebase construction of key candidate genes and pathways in age-related macular degeneration.

Age-related macular degeneration is a retinal disease that severely impacts vision in the older population. Its gene-related heterogeneity has not bee...

GFPrint™: A machine learning tool for transforming genetic data into clinical insights.

The increasing availability of massive genetic sequencing data in the clinical setting has triggered the need for appropriate tools to help fully expl...

Deep learning-enhanced automated mitochondrial segmentation in FIB-SEM images using an entropy-weighted ensemble approach.

Mitochondria are intracellular organelles that act as powerhouses by breaking down nutrition molecules to produce adenosine triphosphate (ATP) as cell...

Novel design of fractional cholesterol dynamics and drug concentrations model with analysis on machine predictive networks.

Within the intricate fabric of human physiology, cholesterol, a lipid present in cell membranes exerts a discernible effect on the concentration of th...

Identification of Taihang-chicken-specific genetic markers using genome-wide SNPs and machine learning: BREED-SPECIFIC SNPS OF TAIHANG CHICKEN.

Taihang is an indigenous breed in Hebei Province and has a long history of evolution. To uncover the genetic basis and protect the genetic resources, ...

Detection of motor nervous disease using deep learning based Duple feature extraction network.

BackgroundA motor nervous disease (MND) is a debilitating nervous disease that affects motor neurons that regulates the muscular voluntary movements. ...

Exploring sensory alterations and repetitive behaviors in children with autism spectrum disorder from the perspective of artificial neural networks.

BACKGROUND: Restrictive repetitive behaviors (RRBs) and sensory processing disorders are core symptoms of autism spectrum disorder (ASD). Their relati...

Early diagnostic value of home video-based machine learning in autism spectrum disorder: a meta-analysis.

UNLABELLED: Machine learning (ML) based on remote video has shown ideal diagnostic value in autism spectrum disorder (ASD). Here, we conducted a meta-...

Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

There exist significant challenges for lung adenocarcinoma (LUAD) due to its poor prognosis and limited treatment options, particularly in the advanc...

Deep learning enabled integration of tumor microenvironment microbial profiles and host gene expressions for interpretable survival subtyping in diverse types of cancers.

The tumor microbiome, a complex community of microbes found in tumors, has been found to be linked to cancer development, progression, and treatment o...

Wearable EEG Neurofeedback Based-on Machine Learning Algorithms for Children with Autism: A Randomized, Placebo-controlled Study.

OBJECTIVE: Behavioral interventions have been shown to ameliorate the electroencephalogram (EEG) dynamics underlying the behavioral symptoms of autism...

A Parkinson's disease-related nuclei segmentation network based on CNN-Transformer interleaved encoder with feature fusion.

Automatic segmentation of Parkinson's disease (PD) related deep gray matter (DGM) nuclei based on brain magnetic resonance imaging (MRI) is significan...