Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Longitudinal Assessment of DNA Repair Signature Trajectory in Prodromal versus Established Parkinson’s Disease

Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-...

Metabolomic and transcriptomic signature in Kabuki syndrome

Kabuki Syndrome (KS) is a rare multisystem disorder with a variable clinical phenotype. The majority...

Dissecting the genetic complexity of myalgic encephalomyelitis/chronic fatigue syndrome via deep learning-powered genome analysis

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogeneous, and systemi...

Development and validation of genomic biotypes for schizophrenia susceptibility from multiple polygenic scores

Understanding the genetic architecture of schizophrenia (SCZ) is invaluable for the development of p...

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. T...

Clinical Evaluation of an AI System for Streamlined Variant Interpretation in Genetic Testing

The growing use of exome/genome sequencing to diagnose hereditary diseases has increased the interpr...

AI enabled exome and transcriptome liquid biopsy platform spanning the continuum of care in oncology

Effective clinical management of patients with cancer requires highly accurate diagnosis, precise th...

Artificial intelligence in clinical genetics: current practice and attitudes among the clinical genetics workforce

Artificial intelligence (AI) applications for clinical genetics hold the potential to improve patien...

Deep learning-based polygenic scores enhance generalizability of psychiatric disorders prediction

Polygenic scores (PGSs) have emerged as promising tools for predicting complex traits from genetic d...

Identification of (ultra-)rare functional promoter mutations in cancer using sequence-based deep learning models

The identification of non-coding somatic cancer-driver mutations remains challenging due to difficul...

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder Cancer

Muscle-invasive bladder cancer (MIBC) is associated with poor predictability of response to cisplati...

Multiple instance fine-mapping: predicting causal regulatory variants with a deep sequence model

Identifying causal genetic variants in a computational manner remains an open problem. Training end-...

Integrative Machine Learning Approach to Risk Prediction for Dementia and Alzheimer’s Disease

Dementia, especially Alzheimer’s disease (AD), is a major global health challenge marked by progress...

Exploring Novel Kinetics of Automated H2O2 Nebulization: A Breakthrough in SARS-CoV-2 Elimination

Although hydrogen peroxide (H2O2) nebulization has shown promise for reducing SARS-CoV-2 loads in he...

DeepSeek as the paradigm shift in rare disease diagnosis – the power of a fully automated genetic variant classification system

Large language models (LLMs) have been extensively tested for incorporating into medical application...

Machine Learning-Based Identification of Sickle Cell Disease Subphenotypes in Clinical Trial Data

Sickle Cell Disease (SCD) is a rare autosomal recessive disorder caused by a point mutation producin...

Granular Insights:A Wastewater-Based Machine Learning Approach for Localized COVID-19 Hospitalization Forecasting

Wastewater based epidemiology (WBE) is a valuable tool for monitoring emerging disease trends in a c...

Decomposing patient heterogeneity of single-cell cancer data by cross-attention neural networks

Gene expression variation in cancer cells is attributed to many inherited and environmental factors,...

Artificial intelligence for precision oncology: AI-HOPE-MAPK uncovers clinically actionable MAPK alterations in colorectal cancer

The emergence of early-onset colorectal cancer (EOCRC), particularly among populations with dispropo...

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