Neurology

Autism

Latest AI and machine learning research in autism for healthcare professionals.

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AI-enabled clinical decision support tools for mental healthcare: A product review.

The review seeks to promote transparency in the availability of regulated AI-enabled Clinical Decisi...

A pilot evaluation of school-based LEGO® robotics therapy for autistic students.

There is emerging evidence that LEGO® therapy is an effective way of supporting younger autistic chi...

Representing DNA for machine learning algorithms: A primer on one-hot, binary, and integer encodings.

This short paper presents an educational approach to teaching three popular methods for encoding DNA...

Enhancing Autism Detection Through Gaze Analysis Using Eye Tracking Sensors and Data Attribution with Distillation in Deep Neural Networks.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by differences in soc...

Using deep learning to classify developmental differences in reaching and placing movements in children with and without autism spectrum disorder.

Autism Spectrum Disorder (ASD) is among the most prevalent neurodevelopmental disorders, yet the cur...

Artificial neural network for evaluating sleep spindles and slow waves after transcranial magnetic stimulation in a child with autism.

Sleep spindles (SS) and slow waves (SW) serve as indicators of the integrity of thalamocortical conn...

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 interventio...

Design of Recyclable Plastics with Machine Learning and Genetic Algorithm.

We present an artificial intelligence-guided approach to design durable and chemically recyclable ri...

Machine learning based metabolomic and genetic profiles for predicting multiple brain phenotypes.

BACKGROUND: It is unclear regarding the association between metabolomic state/genetic risk score(GRS...

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) bund...

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 outco...

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) formulation...

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...

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...

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 ...

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 popu...

Preliminary Screening for Hereditary Breast and Ovarian Cancer Using an AI Chatbot as a Genetic Counselor: Clinical Study.

BACKGROUND: Hereditary breast and ovarian cancer (HBOC) is a major type of hereditary cancer. Establ...

A hybrid deep learning model-based LSTM and modified genetic algorithm for air quality applications.

Over time, computing power and storage resource advancements have enabled the widespread accumulatio...

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...

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