Neurology

Autism

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

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Characterizing feral swine movement across the contiguous United States using neural networks and genetic data.

Globalization has led to the frequent movement of species out of their native habitat. Some of these...

Optimizing cancer diagnosis: A hybrid approach of genetic operators and Sinh Cosh Optimizer for tumor identification and feature gene selection.

The identification of tumors through gene analysis in microarray data is a pivotal area of research ...

Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.

BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches prima...

An initial exploration of machine learning for establishing associations between genetic markers and THC levels in Cannabis sativa samples.

Cannabis sativa, a globally commercialized plant used for medicinal, food, fiber production, and rec...

A multicenter study on deep learning for glioblastoma auto-segmentation with prior knowledge in multimodal imaging.

A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for r...

Family history of cancer and lung cancer: Utility of big data and artificial intelligence for exploring the role of genetic risk.

OBJECTIVES: Lung Cancer (LC) is a multifactorial disease for which the role of genetic susceptibilit...

A Secure High-Order Gene Interaction Detection Algorithm Based on Deep Neural Network.

Identifying high-order Single Nucleotide Polymorphism (SNP) interactions of additive genetic model i...

Duple-MONDNet: duple deep learning-based mobile net for motor neuron disease identification.

BACKGROUND/AIM: Motor neuron disease (MND) is a devastating neuron ailment that affects the motor ne...

Enhancing schizophrenia phenotype prediction from genotype data through knowledge-driven deep neural network models.

This article explores deep learning model design, drawing inspiration from the omnigenic model and g...

Machine learning-enabled detection of attention-deficit/hyperactivity disorder with multimodal physiological data: a case-control study.

BACKGROUND: Attention-Deficit/Hyperactivity Disorder (ADHD) is a multifaceted neurodevelopmental psy...

Advancing plant biology through deep learning-powered natural language processing.

The application of deep learning methods, specifically the utilization of Large Language Models (LLM...

Comparison of three artificial intelligence algorithms for automatic cobb angle measurement using teaching data specific to three disease groups.

Spinal deformities, including adolescent idiopathic scoliosis (AIS) and adult spinal deformity (ASD)...

Machine Learning Prediction of Autism Spectrum Disorder From a Minimal Set of Medical and Background Information.

IMPORTANCE: Early identification of the likelihood of autism spectrum disorder (ASD) using minimal i...

A comprehensive multi-task deep learning approach for predicting metabolic syndrome with genetic, nutritional, and clinical data.

Metabolic syndrome (MetS) is a complex disorder characterized by a cluster of metabolic abnormalitie...

Speech and language patterns in autism: Towards natural language processing as a research and clinical tool.

Speech and language differences have long been described as important characteristics of autism spec...

Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morpholo...

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