Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 38,481 to 38,490 of 223,469 articles

Predicting Unseen Gene Perturbation Response Using Graph Neural Networks with Biological Priors

bioRxiv
Predicting transcriptional responses to genetic perturbations is a central challenge in functional genomics. CRISPR Perturb-seq experiments measure gene expression changes induced by targeted perturbations, yet experimentally testing all possible per... read more 

Scaling and Generalization of Discrete Diffusion Models for Tumor Phylogenies

bioRxiv
Tumor phylogenies - rooted trees encoding clonal ancestry and mutation acquisition - are central to understanding cancer evolution, yet generating realistic phylogenies remains challenging. We investigate whether discrete graph diffusion can learn th... read more 

Age-related cerebellar genetic, neuronal and functional impairments are reversed by specific magnetic stimulation protocols

bioRxiv
Age-related cognitive decline reflects progressive atrophic changes that advance through broad neural networks. There is no effective treatment. However, brain ageing is not homogenous, so treating the earliest-affected circuits may be successful in ... read more 

FoundedPBI: Using Genomic Foundation Models to predict Phage-Bacterium Interactions

bioRxiv
The scalability of phage therapy as a viable alternative or complement to antibiotics is limited by the labor-intensive experimental screening required to identify compatible phage-bacterium pairs. To accelerate this discovery process, we propose Fou... read more 

Inferring seagrass meadow resilience from self-organized spatial patterns

bioRxiv
Assessing ecosystem resilience at large spatial scales remains a major challenge in ecology and conservation. While resilience is typically inferred from temporal dynamics or perturbation experiments, ecosystems governed by spatial self-organization ... read more 

OPTIMIS: Optimizing Personalized Therapies through Integrated Multiscale Intelligent Simulation

bioRxiv
Controlling complex biological systems across multiple scales remains a major challenge in computational medicine, because whole-body disease behavior is closely shaped by noisy cellular events at much smaller scales. Standard deterministic models of... read more 

Self-supervised learning for a gene program-centric view of cell states

bioRxiv
Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensiona... read more 

Evaluating Evo 2 for plant variant effect prediction

bioRxiv
The genomic foundation model Evo 2 enables zero-shot variant effect prediction. Here, we evaluate its performance using Arabidopsis thaliana reproductive barrier genes with experimentally confirmed gain- and loss-of-function variants, and show that E... read more 

Spectral and non-spectral EEG measures in the prediction of working memory task performance and psychopathology

bioRxiv
Working memory (WM) supports the temporary maintenance of goal-relevant information and is disrupted across many neuropsychiatric disorders. We examined whether scalp electroencephalography (EEG) data features beyond spectral power, including wavefor... read more 

WINDEX: A hierarchical integration of site- and window-based statistics for characterizing the footprint of positive selection in genome-wide population genetic data

bioRxiv
Adaptive mutations, or mutations that confer a fitness benefit, can leave behind distinct signals in genetic data. Computational methods have improved the localization of adaptive mutations in genetic samples using a range of statistical and machine ... read more