Latest AI and machine learning research in genetics for healthcare professionals.
Genomic foundation models pretrained on DNA sequence have achieved strong performance across a range of tasks, but sequence-only representations cannot fully capture regulatory information reflected by additional DNA-centric modalities. Existing multimodal genomic models are often optimized for specific prediction tasks rather than for learning reusable embeddings shared across downstream analyses...
Lung cancer screening with low-dose chest computed tomography reduces mortality, but its impact is limited by uptake, adherence, and management challenges. Blood-based cell-free DNA (cfDNA) biomarkers offer a complementary approach, although early detection remains difficult because of lung cancer heterogeneity and high-dimensional, nonlinear molecular signals. We evaluated quantum-classical hybri...
Progress in precision oncology, including biomarker discovery and individualized treatment selection, is limited by the complexity of clinico-genomic ...
Abstract Background: Every non-invasive continuous glucose monitoring (NI-CGM) technology introduced into the landscape faces the same skeptical quest...
Predicting gene expression from DNA sequence across diverse genomic tracks is essential for understanding gene regulation and interpreting non-coding ...
Background: Phenotype-genotype associations underpin precision medicine by enabling disease prevention, early diagnosis, risk stratification, therapeu...
Global incidence and outcomes of glioma have been found to vary significantly by region, however research into the disease continues to lack diversity...
Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable ge...
Isocitrate dehydrogenase (IDH) mutant gliomas often transform from low to high grade aggressive tumors. The genetic and molecular drivers of this Mali...
Comprehensive analyses of whole-genome and exome sequencing data from high-risk neuroblastoma tumors have revealed relatively few recurrent, clinicall...
Long-range vision-based deformation monitoring is highly sensitive to motion of the camera platform. Absolute-pose differencing typically relies on de...
Human milk contains a diverse array of metabolites that contribute to infant nutrition, immune development, and microbial colonization. The maternal f...
Three-dimensional chromatin interactions shape gene regulation, but their large-scale analysis remains limited by the cost and complexity of experimen...
Detecting AI-generated images is only half the task: a deployed detector must also justify its verdict, yet existing detectors inherit three failure m...
Text-Image-to-Video (TI2V) models are an emerging unified architecture, where a single model simultaneously supports text-to-video (T2V) and image-to-...
Medical foundation models learn latent representations of clinically meaningful phenotypes, yet their ability to support controllable image generation...
Hypertrophic and dilated cardiomyopathy (HCM and DCM) carry substantial morbidity and mortality, yet diagnosis may be delayed, particularly when prese...
Large Vision-Language Models (LVLMs) integrate visual perception with language generation, enabling responses that span image understanding and comple...
Generative models can produce images nearly indistinguishable from real data, yet rigorous and interpretable evaluation remains challenging. Conventio...
High-dimensional population balance equations (PBEs) provide a natural framework for modeling heterogeneous cell populations, but their direct numeric...