Genetics

DEEP LEARNING-BASED PHENOTYPING OF FOREFOOT MORPHOLOGY IN HEREDITARY THORACIC AORTIC DISEASES

Hereditary thoracic aortic diseases (HTAD) are often associated with multifaceted phenotypic manifestations in different anatomical districts, including skeletal abnormalities. Therefore, diagnostic criteria account for multiple parameters to compute a systemic risk score. Despite the forefoot is known to be different in HTAD, its complex morphology is difficult to be quantified objectively and it...

Assessing Genotype-Phenotype Correlations with Deep Learning in Colorectal Cancer: A Multi-Centric Study

Deep Learning (DL) has emerged as a powerful tool to predict genetic biomarkers directly from digitized Hematoxylin and Eosin (H&E) slides in colorectal cancer (CRC). However, few studies have systematically investigated the predictability of biomarkers beyond routinely available alterations such as microsatellite instability (MSI), and BRAF and KRAS mutations. Our primary dataset comprised H&E sl...

AI-HOPE: An AI-Driven conversational agent for enhanced clinical and genomic data integration in precision medicine research

Introduction: The increasing complexity of clinical cancer research necessitates the development of automated tools capable of integrating clinical an...

MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide intermediate phenotypes (i.e., endophenotypes) that bri...

Evaluation of Machine Learning and Traditional Statistical Models to Assess the Value of Stroke Genetic Liability for Prediction of Risk of Stroke within the UK Biobank

Stroke is one of the leading causes of mortality and long-term disability in adults over 18 years of age globally and its increasing incidence has bec...

Development and validation of a machine learning model to predict cognitive behavioral therapy outcome in obsessive-compulsive disorder using clinical and neuroimaging data

Cognitive behavioral therapy (CBT) is a first-line treatment for obsessive-compulsive disorder (OCD), but clinical response is difficult to predict. I...

RNAseq-Based Machine Learning Models for Prognostication of Multiple Myeloma

Multiple myeloma (MM) is characterized by abnormal plasma cell proliferation in the bone marrow, leading to symptoms like osteolytic lesions, anemia, ...

Machine learning-based analysis of genomic and transcriptomic data unveils sarcoma clusters with superlative prognostic and predictive value

Soft tissue sarcomas (STS) histopathological classification system has several conceptual caveats, impacting prognostication and treatment. The clinic...

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

Biological aging clocks across organs and omics data, including clinical phenotypes, neuroimaging, proteomics, and epigenetics, have proven instrument...

Leveraging functional annotations to map rare variants associated with Alzheimer’s disease with gruyere

The increasing availability of whole-genome sequencing (WGS) has begun to elucidate the contribution of rare variants (RVs), both coding and non-codin...

Data-driven consideration of genetic disorders for global genomic newborn screening programs

Over 30 international studies are exploring newborn sequencing (NBSeq) to expand the range of genetic disorders included in newborn screening. Substan...

Genetic variants risk assessment for Long QT Syndrome through machine learning and multielectrode array recordings

Long QT syndrome (LQTS) is a life-threatening genetic disorder characterized by prolonged QT intervals on electrocardiograms. Congenital forms are mos...

Establishment of in silico prediction of adjuvant chemotherapy response from active mitotic gene signature in non-small cell lung cancer

Conventional chemotherapeutics exploit cancer’s hallmark of active cell cycling, primarily targeting mitotic cells. Consequently, the mitotic index (M...

Pan-Omics Fusion and Machine Learning Unveil Congenital Tooth Agenesis-Ecto-mesodermal Diseases Link and Biomarker Discovery

Congenital tooth agenesis (CTA) is a common developmental anomaly with complex genetic and molecular mechanisms. Previous studies have primarily focus...

Analysis of genetic overlap between inborn errors of immunity and neurodevelopmental disorders

Inborn errors of immunity (IEI), formerly known as primary immune deficiencies (PID), are a group of genetic disorders that affect the immune system, ...

Genetic Architecture and Risk Prediction of Gestational Diabetes Mellitus in over 116,144 Chinese Pregnancies

Gestational diabetes mellitus (GDM), a heritable metabolic disorder and the most common pregnancy-related condition, remains understudied regarding it...

Encoding of pretrained large language models mirrors the genetic architectures of human psychological traits

Recent advances in large language models (LLMs) have prompted a frenzy in utilizing them as universal translators for biomedical terms. However, the b...

AI-Driven Fluorescence Peak Analysis for Chromosomal Aneuploidy Detection: A Python-Based Machine Learning Approach for Enhanced Accuracy and Efficiency

Chromosomal aneuploidy, a condition characterized by an abnormal number of chromosomes, is a major genetic disorder affecting human reproduction, lead...

A Prospective Cohort Study to Develop Multi-Biomarkers Panel to Define Biological Ageing in Five Different Cohorts from Newborn to Oldest Adult: A Study Protocol

Age-associated disease management depends significantly on chronological age and macro-level clinical data sets. However, the biological age captures ...

Artificial Intelligence algorithm for real-time detection and counting of Trypanosoma cruzi parasites using smartphone microscopy

Chagas disease affects 6–7 million people worldwide and causes approximately 12,000 deaths annually. Diagnostic methods vary by disease stage, with se...