Autism

Precision dermatology 2050: AI-driven personalized monitoring and individualized treatment.

By 2050, advances in artificial intelligence (AI), Internet of Medical Things (IoMT) and teledermatology are predicted to fundamentally transform the diagnosis and management of chronic inflammatory skin conditions. This white paper examines the anticipated patient journey in 2050, emphasizing personalized, technology-driven healthcare approaches that integrate innovations in discovery, diagnosis,...

Genetic and epigenetic determinants of injury risk and recovery in elite athletes: toward precision sports medicine.

Musculoskeletal injuries and interindividual variability in recovery remain critical challenges for sustaining elite athletic performance. Despite advances in diagnostics, training, and rehabilitation, unexplained differences in injury risk and recovery efficiency persist. Growing evidence implicates genetic and epigenetic mechanisms in these disparities, influencing collagen integrity, inflammato...

Adaptive network based fuzzy inference system efficientnet for autism spectrum disorder detection with optimization based pivotal region extraction.

Autism Spectrum Disorder (ASD) refers to abnormal neural activity that may increase the risk of premature brain development issues. Many traditional t...

Using, misusing, and improving online machine learning-based meta-analysis of neuroimaging published data: A perspective on NeuroQuery.

Online, text-based meta-analysis tools for large databases represent a new digital advance for medical, health, and neuroscience research, among other...

Multimodal-based deep learning detected disrupted precuneus connectivity and its related genetic profiles for predicting adults with ADHD.

BACKGROUND: Integrating neuroimaging genetics data may enhance the diagnosis and understanding of adults with attention-deficit/hyperactivity disorder...

Emerging biomarkers in prostate cancer diagnosis and treatment: Insights into genetic, RNA and metabolic markers (Review).

Prostate cancer remains one of the most prevalent malignancies and a major cause of cancer‑related mortality among men worldwide. Despite widespread u...

Bioinformatics applications in pharmacogenomics: towards personalized medicine.

Pharmacogenomics investigates how genetic variation influences individual responses to drug therapy and aims to optimize treatment outcomes through pe...

Genomic assessment of reproduction traits in Holstein dairy cattle across 3 lactations using additive genetic models and post hoc random forest analysis.

The typical objective of genomic analyses is to assess additive genetic variance in traits. However, the nonadditive component of genetic variation is...

Pathway-Informed Machine Learning Identifies Genetic Predictors of High-Dose Methotrexate-Induced Mucositis in Pediatric Acute Lymphoblastic Leukemia.

High-dose methotrexate for pediatric cancer treatment is frequently associated with mucositis, which can lead to delayed or discontinued treatment and...

Graph-level contrastive learning with self-aware and cross-sample topology augmentation for brain disorder diagnosis using rs-fMRI.

Resting-state functional MRI (rs-fMRI) is widely used for diagnosing and analyzing brain disorders. However, existing fMRI studies have shown that lea...

EIOFX-DT: Leveraging graph centrality metrics for feature extraction and classification of viral genetic sequences.

Many diseases have a genetic origin, and analyzing intracellular structures through genetic data yields specific features for the diagnosis and classi...

Deep learning for autism detection using clinical notes: A comparison of transfer learning for a transparent and black-box approach.

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition whose rising prevalence places increasing demands on a lengthy diagnostic pro...

Revisiting KANET in the context of fetal connectomics: defining optimal gestational windows for neurodevelopmental screening.

OBJECTIVES: To introduce the KANET-connectome matrix (KANET-Con) as a conceptual framework linking fetal behaviors observed on four-dimensional (4D) u...

A coupled spiking neural P system integrated with two-level neighborhood search for solving flexible job shop scheduling problems.

The Flexible Job Shop Scheduling Problem (FJSP) is an Non-deterministic Polynomial (NP)-hard combinatorial optimization problem whose large-scale and ...

Advances in antituberculosis drug-induced liver injury: Molecular mechanisms, genetic insights, and emerging animal-free prediction models.

Approximately 10 million tuberculosis patients worldwide require drug therapies annually. However, prolonged use of tuberculocidal drugs in combinatio...

Identification of common genetic features and pathways for osteoporosis with frozen shoulder by integrated bioinformatics analysis and machine learning.

Frozen shoulder (FS) and osteoporosis (OP) are common age-related degenerative diseases, occurring more frequently in females, which suggests potentia...

Guiding design and performance of nonviral nucleic acid delivery vehicles via machine learning.

Machine Learning (ML) techniques have enabled the advancement of many technologies throughout the pharmaceutical industry, especially for drug discove...

Molecular targeted therapies, omics, and AI based theranostics approaches for the treatment of prostate cancer.

Cancer is a disease that begins with genetic and epigenetic alterations occurring in specific cells, some of which can spread and migrate to other tis...

Molecular pathways of kidney development and their applications to clinical research.

Congenital anomalies of the kidney and urinary tract (CAKUT) are the major cause of childhood chronic kidney disease and an antecedent cause of adult-...

Prediction and genetic analysis of blood β-hydroxybutyrate based on milk mid-infrared spectra in Fleckvieh dairy cows.

Hyperketonemia is a common metabolic disorder in early-lactation dairy cows that impairs milk performance and health. The gold-standard indicator for ...