Artificial Intelligence Medical Compendium

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

Showing 44,401 to 44,410 of 224,055 articles

Automated high-throughput fabrication of patient-specific vessel-on-chips enables a generative AI digital twin--Cascade Learner of Thrombosis (CLoT) for personalized thrombosis prediction

bioRxiv
We developed an integrated platform combining high-throughput automated biofabrication, systematic patient-derived tissue experiments, and specialized artificial intelligence to enable patient-specific computational "digital twins" for thrombosis pre... read more 

A Machine Learning Framework for Serogroup Classification of pathogenic species of Leptospira Based on rfb Locus Profiles

bioRxiv
Leptospira is a highly diverse genus traditionally classified by serological assays into more than 30 serogroups and over 300 serovars. However, this classification system is often complex and inconsistent, as cross-reactions between antigens can lea... read more 

Predicting how perturbations reshape cellular trajectories with PerturbGen

bioRxiv
A major challenge in biology is predicting how cells transition between states over time and how perturbations disrupt these transitions. Understanding such dynamics is critical for identifying interventions that reverse pathological programs or repr... read more 

Tabular foundation model predicts alternative lengthening of telomeres (ALT) and identifies SMARCAL1 as a target in ALT-driven cancers

bioRxiv
Alternative lengthening of telomeres (ALT) is a telomerase-independent pathway used by aggressive cancers to maintain their replicative immortality. Because ALT is absent from normal human cells, it is an appealing target for cancer therapy, but the ... read more 

Streak-Aware Localization Microscopy Enables High-Throughput Brain Imaging Across Platforms

bioRxiv
Optical, ultrasound, and optoacoustic localization microscopy based on microparticle tracking has enabled surpassing the resolution limits imposed by ultrasound diffraction and optical diffusion in tissues. However, its reliance on high-speed (kilohe... read more 

A high-throughput method for measuring fungal growth rate on solid media using automated imaging and deep learning

bioRxiv
Measuring the growth rate of filamentous fungi is an essential phenotype assay in fungal biology, enabling the comparison of nutrient-related fitness metrics across various isolates, species and genera. Conventional methods are time consuming and lab... read more 

Grounding olfactory perception in language: Benchmarks and models for generating natural language odor descriptions

bioRxiv
Recent advances in deep learning have enabled prediction of odorant perception from molecular structure, opening new avenues for odor classification. However, most existing models are limited to predicting percepts from fixed vocabularies and fail to... read more 

Functional Locality-Aligned Learning Reveals Structure-Function Causality in Enzyme Kinetics

bioRxiv
Accurate estimation of enzyme kinetic parameters is essential for enzyme engineering and industrial biocatalysis, yet their experimental measurement remains labor-intensive and costly. Although machine learning offers an efficient alternative, existi... read more 

Leveraging publicly available datasets and machine learning approaches for predicting the health benefits of fermented foods

bioRxiv
Fermented foods are an ancient, near universal component of human dietary culture and are increasingly recognized for their health benefits. Bioactive peptides and biosynthetic gene clusters (BGCs) produced by microbes during fermentation have been s... read more 

Massive-scale single-nucleus multi-omics identifies novel rare noncoding drivers of Parkinson's disease

bioRxiv
Most genetic variants contributing to complex diseases reside in the noncoding genome. While common variants uncovered by genome-wide association studies often fail to explain much of the observed heritability of these diseases, rare variants often h... read more