Artificial Intelligence Medical Compendium

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

Showing 12,201 to 12,210 of 210,314 articles

Performance of IBD machine learning classifiers varies across microbiome training data independent of geographic diversity

bioRxiv
Microbiome-based machine learning classifiers show increasing promise for disease identification across gastrointestinal, metabolic, and immune-mediated conditions. Inflammatory bowel disease (IBD), a chronic immune-mediated disorder associated with ... read more 

Robust Random Forests for Genomic Prediction: Challenges and Remedies

bioRxiv
Data contamination, from recording errors to extreme outliers, can compromise statistical models by biasing predictions, inflating prediction errors, and, in severe cases, destabilizing performance in high-dimensional settings. Although contamination... read more 

Large-Scale Assessment of Animal-to-Human Drug Translation Using Natural Language Processing

bioRxiv
Background: Large-scale estimates of animal-to-human drug translation and the study characteristics associated with successful translation remain limited. The expanding preclinical literature also challenges manual evidence synthesis. We developed a ... read more 

Application of modern mathematical methods for species discrimination in the water fleas (Cladocera: Branchiopoda) that appear similar to the human eye: case of Bosmina (Bosmina) longirostris (O.F. Muller, 1776) from European Eurasia and Sakhalin Island

bioRxiv
Intraspecific morphological variability presents a complex challenge for biological systematics and biomonitoring, particularly for organisms with high phenotypic plasticity, such as zooplankton. Morphological differences between individuals of the w... read more 

Internal state dynamically gates task-specific attractor dynamics in prefrontal cortex

bioRxiv
Internal states such as motivation and task engagement influence cognitive functions. Working memory, which maintains information over time, is an essential component of cognition and is modulated by motivation. Here, we show motivational states modu... read more 

A Competitive Framework for Modeling EEG Microstate Durations

bioRxiv
Background. This study examines a competition based model (Cmodel) designed to capture the temporal dynamics of successive brain microstates derived from electroencephalography (EEG) recordings during eyes-open conditions. The analyzed data were obta... read more 

A community machine learning challenge to predict the effects of gene perturbations on T cell differentiation for cancer immunotherapy

bioRxiv
Perturbations of genes with functional importance in T cells could be used to change the distribution of CD8 T cell states to enhance anti-tumor functions for cancer immunotherapies. We launched a world-wide computational challenge to predict the eff... read more 

Generalist large language models complement tailor-made predictors for tumor genomics interpretation

bioRxiv
General-purpose large language models (LLMs) are trained on large corpora to acquire broad knowledge, but whether LLMs can replace, or augment, task-specific models is unclear. We evaluated LLMs on three real-world, clinically important tumor genomic... read more 

De novo design of RNA pseudoknots with deep learning

bioRxiv
RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an E... read more 

Estimating bone marrow adiposity from head MRI and identifying its genetic architecture

medRxiv
Bone marrow adiposity changes radically through the lifespan, but this phenomenon is poorly characterised and understood in humans. Large datasets of magnetic resonance imaging (MRI) scans of the head have been collected to study the human brain, but... read more