Autism

Comprehensive framework for thyroid disorder diagnosis: Integrating advanced feature selection, genetic algorithms, and machine learning for enhanced accuracy and other performance matrices.

Thyroid hormones control crucial physiological activities, such as metabolism, oxidative stress, erythropoiesis, thermoregulation, and organ development. Hormonal imbalances may cause serious conditions like cognitive impairment, depression, and nervous system damage. Traditional diagnostic techniques, based on hormone level measurements (TSH, T3, FT4, T4, and FTI), are usually lengthy and laborio...

Morphological traits and machine learning for genetic lineage prediction of two reef-building corals.

Integrating multiple lines of evidence that support molecular taxonomy analysis has proven to be a robust method for species delimitation in scleractinian corals. However, morphology often conflicts with genetic approaches due to high phenotypic plasticity and convergence. Understanding morphological variation among species is crucial to studying coral distribution, life history, ecology, and evol...

AI-driven techniques for detection and mitigation of SARS-CoV-2 spread: a review, taxonomy, and trends.

The SARS-CoV-2 RNA virus, with its rapid spread and frequent genetic changes, has posed unparalleled obstacles for public health and treatment efforts...

From neurotoxicity to neuroprotection: Rethinking GABAR-targeting anesthetics.

The brain growth spurt (BGS) represents a pivotal window in neurodevelopment, defined by rapid neurogenesis, heightened synaptogenesis, and the dynami...

Optimizing stroke detection with genetic algorithm-based feature selection in deep learning models.

Brain stroke is a leading cause of disability and mortality worldwide, necessitating the development of accurate and efficient diagnostic models. In t...

Stereotactic Body Radiation Therapy for Primary Renal Cancer and Genetic Markers of Response: A Phase 2 Trial.

Controlled outcome assessment of radiotherapy for primary renal cell carcinoma (RCC) remains limited, particularly regarding its impact on ipsilateral...

Advanced molecular approaches to thalassemia disorder and the selection of molecular-level diagnostic testing in resource-limited settings.

Beta-thalassemia is a genetic disorder that significantly burdens healthcare systems globally. This inherited blood disorder, categorized into beta-th...

Neur-Ally: a deep learning model for regulatory variant prediction based on genomic and epigenomic features in brain and its validation in certain neurological disorders.

Large-scale quantitative studies have identified significant genetic associations for various neurological disorders. Expression quantitative trait lo...

Toward a general framework for AI-enabled prediction in crop improvement.

A theoretical framework for AI and ensembled prediction for crop improvement is introduced and demonstrated using the logistic map. Symbolic/sub-symbo...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contri...

Gene as a Molecular Target Potentially Shared by Idiopathic Pulmonary Fibrosis and Pulmonary Hypertension: Drug Repurposing Prospect with Aminoglutethimide.

Idiopathic pulmonary fibrosis (IPF) and pulmonary hypertension (PH) are two chronic conditions that can coexist occasionally, resulting in high morbid...

Linking autism risk genes to morphological and pharmaceutical screening by high-content imaging: Future directions and opinion.

Next-generation sequencing has identified risk genes with large effect sizes for autism spectrum disorders (ASD). Although functional analysis of indi...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble into functional neural networks. Studies investigat...

Machine learning is changing osteoporosis detection: an integrative review.

Machine learning drives osteoporosis detection and screening with higher clinical accuracy and accessibility than traditional osteoporosis screening t...

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.

The increasing demand for population-wide genomic screening and the limited availability of genetic counseling resources have created a pressing need ...

Optimizing Plant Alkaloid Biosynthesis under Drought Stress: Regulatory Mechanisms and Biotechnological Strategies.

Global climate change exacerbates drought stress, severely affecting plant growth, agricultural productivity, and the biosynthesis of secondary metabo...

Explainable Artificial Intelligence (XAI) in the Era of Large Language Models: Applying an XAI Framework in Pediatric Ophthalmology Diagnosis using the Gemini Model.

Amblyopia is a neurodevelopmental disorder affecting children's visual acuity, requiring early diagnosis for effective treatment. Traditional diagnost...

Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (...

Personalized deep neural networks reveal mechanisms of math learning disabilities in children.

Learning disabilities affect a substantial proportion of children worldwide, with far-reaching consequences for their academic, professional, and pers...

Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

Origin tracking is important to ensure use of the right seed source and trade with legally harvested timber. Additionally, it can help to reconstruct ...