Autism

Integration of inter-simple sequence repeats with machine learning approach for diversity analysis and authentication of Iranian cotton cultivars.

Cotton (Gossypium hirsutum L.) has experienced extensive breeding in recent decades, leading to a narrowed genetic base that presents challenges for accurate germplasm differentiation and cultivar authentication. This study primarily addresses the lack of reliable, scalable, and interpretable tools for distinguishing closely related Iranian cotton cultivars. To overcome this limitation, the resear...

Examining attention- deficit/ hyperactivity disorder in endurance and ultra-endurance runners.

BACKGROUND: Attention-deficit hyperactivity disorder (ADHD) is a multifactorial and complex neurodevelopmental disorder. Prevalence of ADHD in the general adult population is around 3.1 %, with little data available in athlete population suggesting rates of between 7 %-8 %. No data are available for endurance and ultra-endurance runners. METHODS: Cross-sectional survey study in endurance (≥21.1 km...

The effect of spatial and intensity level augmentation of structural magnetic resonance images on autism diagnosis model.

In deep learning, the robustness and generalizability of models significantly depend on diverse and heterogeneous training data. Acquiring such an ext...

Bridging process diversity in cell therapies toward standardization of manufacturing workflows.

Cell therapies offer transformative potential for a wide range of diseases. However, their manufacturing remains complex due to the inherent variabili...

Synergistic integration of clinical and multi-omics data for early MCI diagnosis using an attention-based graph fusion network.

BACKGROUND: Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often ...

Artificial intelligence in diagnostic, prognostic, and predictive genomic biomarkers for prostate cancer: Ready for prime time?

INTRODUCTION: Until recently, the widespread use of genetic markers in prostate cancer (PCa) has been limited by the complexities and cost of genomic ...

NeuMTL: A Unified Multimodal Framework for Multi-Task Prediction in CNS Drug Discovery.

Deep learning has made significant progress in drug discovery. However, most existing models are single-task and single-modality, which not only limit...

Enlarged cavum septum pellucidum & increased incidence of schizophrenia: Narrative review for neurodevelopmental correlate.

Schizophrenia being a major psychiatric disorder comprises of dominant neurodevelopmental corroborations; still there are inadequate markers which rev...

Neurodevelopmental disabilities among children and adolescents: perspectives and priorities in low- and middle-income countries.

PURPOSE OF REVIEW: To synthesize recent evidence on neurodevelopmental disorders (NDDs) among children and adolescents in low- and middle-income count...

Synthetic data generation in paediatrics and paediatric nursing: what, how, and why?

INTRODUCTION: This paper explores the potential benefits and limitations of synthetic data (SD) in paediatrics, addressing the challenges of data scar...

Polyploid giant cancer cells: A novel target in future cancer therapy.

Under intense therapeutic stress-including chemotherapy, radiotherapy, and targeted therapies-tumor cells can undergo ploidy reprogramming to generate...

Machine learning-based diagnosis of autism spectrum disorder in children and adolescents using eye-tracking data: a systematic review and meta-analysis.

OBJECTIVE: Eye-tracking technology has been increasingly investigated as an objective approach for distinguishing individuals with Autism Spectrum Dis...

Are social robots more interesting than humans? Quantitative assessment of Joint Attention in autistic and typically developing children.

INTRODUCTION: Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication, including joint attention (JA) impa...

A new approach in autism diagnosis: Evaluating natural interaction using point of view (POV) glasses.

This study introduces an AI-assisted method based on examiner-worn Point of View (POV) glasses and computer vision analysis to provide objective behav...

Support vector machine classification of 18F-FDG PET scans across subtypes of amyotrophic lateral sclerosis.

PURPOSE: While 18F-FDG PET imaging has demonstrated diagnostic value in people with Amyotrophic Lateral Sclerosis (PwALS) and group-level differences ...

Neuroinflammation and insulin resistance in major depression and bipolar disorder: Implications for clinical trials evaluating immunometabolic targeted therapies.

Bipolar disorder (BD) and major depressive disorder (MDD) are highly prevalent, disabling psychiatric illnesses marked by substantial heterogeneity an...

MLDeCNV: A machine learning approach for predicting copy number variation types in plant genomes.

Copy number variations (CNVs) play a crucial role in shaping genetic diversity and influencing various plant traits. However, existing methods for CNV...

Developmental Brain Age Estimation From MRI Data: A Systematic Review of Deep Learning Approaches and Open Datasets.

Brain age is an emerging concept that reflects complex, time-dependent changes in brain structure, identifying departures from expected neurodevelopme...

Differentiable neural network-based models enable gradient-based optimization for model predictive control of urban drainage networks.

Model predictive control (MPC) improves the use of the hydraulic capacity of an urban drainage network with online optimization, thus reducing overflo...

Structure of the Enterobacter pan-genome is revealed using machine learning.

The growing availability of publicly accessible Enterobacter genomes offers an opportunity to reveal the structure of its pangenome, uncovering the ca...