Autism

SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.

Deciphering cell identity genes is pivotal to understanding cell differentiation, development, and cell identity dysregulation involving diseases. Here, we introduce SCIG, a machine-learning method to uncover cell identity genes in single cells. In alignment with recent reports that cell identity genes (CIGs) are regulated with unique epigenetic signatures, we found CIGs exhibit distinctive geneti...

An Inclusive Foundation Model for Generalizable Cytogenetics in Precision Oncology

Chromosome analysis is vital for diagnosing genetic disorders and guiding cancer therapy decisions through the identification of somatic clonal aberrations. However, developing an AI model are hindered by the overwhelming complexity and diversity of chromosomal abnormalities, requiring extensive annotation efforts, while automated methods remain task-specific and lack generalizability due to the...

Automated Fetal Biometry Assessment with Deep Ensembles using Sparse-Sampling of 2D Intrapartum Ultrasound Images

The International Society of Ultrasound advocates Intrapartum Ultrasound (US) Imaging in Obstetrics and Gynecology (ISUOG) to monitor labour progres...

Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term...

Decoding cancer prognosis with deep learning: the ASD-cancer framework for tumor microenvironment analysis.

Deep learning is revolutionizing biomedical research by facilitating the integration of multi-omics data sets while bridging classical bioinformatics ...

Deep Learning and Explainable AI: New Pathways to Genetic Insights

Deep learning-based AI models have been extensively applied in genomics, achieving remarkable success across diverse applications. As these models g...

Investigating the Genetic Links Between Immune Cell Profiles and Bladder Cancer: A Multidisciplinary Bioinformatics Approach.

: Bladder cancer (BC) is a common malignancy in the urinary system, with an increasing incidence rate. Immune cell infiltration within the tumor micro...

Characterizing ASD Subtypes Using Morphological Features from sMRI with Unsupervised Learning.

In this study, we attempted to identify the subtypes of autism spectrum disorder (ASD) with the help of anatomical alterations found in structural mag...

Electroencephalography estimates brain age in infants with high precision: Leveraging advanced machine learning in healthcare.

Changes in the pace of neurodevelopment are key indicators of atypical maturation during early life. Unfortunately, reliable prognostic tools rely on ...

A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning.

The data acquisition methods are becoming increasingly diverse and advanced, leading to higher data dimensions, blurred classification boundaries, and...

Innovations in maternal-fetal dermatology: A focus on artificial intelligence-driven diagnostics, global disparities, and transformative care.

Pregnancy-associated dermatologic conditions emerge from intricate hormonal, immunologic, genetic, and environmental changes, often complicating mater...

Alzheimer's subtypes A supervised, unsupervised, multimodal, multilayered embedded recursive (SUMMER) AI study.

Since Alzheimer's disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, req...

The frontiers of intelligent health services: cardiovascular disease prediction using novel machine learning methods and metaheuristic algorithm.

Cardiovascular disease (CVD) significantly impacts global mortality and aging. Effective risk assessment relies on models like Linear Discriminant Ana...

Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays.

This paper introduces a versatile and efficient design methodology for optimizing wide-angle impedance matching (WAIM) configurations, enhancing the s...

Development of 3D Intelligent Quantitative Phase Microscope for Sickle Cells Screening.

Sickle cell disease (SCD) is a genetic blood disorder causing red blood cells to deform into a sickle shape, often leading to misdiagnosis. Early dete...

Transcriptomic Profiling of Hypoxia-Adaptive Responses in Tibetan Goat Fibroblasts.

The Tibetan goat () exhibits remarkable adaptations to high-altitude hypoxia, yet the molecular mechanisms remain unclear. This study integrates RNA-s...

Revolutionizing sleep disorder diagnosis: A Multi-Task learning approach optimized with genetic and Q-Learning techniques.

Adequate sleep is crucial for maintaining a healthy lifestyle, and its deficiency can lead to various sleep-related disorders. Identifying these disor...

Next-generation Approaches in Targeting Polycystic Ovarian Syndrome: Innovative Strategies.

Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder that affects millions of women worldwide and is characterized by ovarian dysfunction,...

Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types.

The growing burden of cancer and recent surge in healthcare data availability call for new ways of analysing this multifactorial disease and improving...

Developmental and epileptic or epileptic encephalopathy with spike-wave activation in sleep: From the 'functional ablation' model to a neurodevelopmental network perspective.

The interplay between epilepsy and cognition is intricate and multifaceted, particularly in the context of childhood-onset epileptic disorders where e...