Artificial Intelligence Medical Compendium

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

Showing 43,161 to 43,170 of 223,853 articles

Reassessing Number-Detector Units in Convolutional Neural Networks

bioRxiv
Convolutional neural networks (CNNs) have become essential models for predicting neural activity and behavior in visual tasks. However, their ability to capture higher-level cognitive functions, such as numerosity discrimination, remains debated. Num... read more 

Integrated proteomic screening reveals design principles of CRBN molecular glue degraders

bioRxiv
Cereblon (CRBN)-based molecular glue degraders (MGDs) induce the degradation of diverse disease-relevant proteins, underscoring their broad therapeutic potential. Here we systematically expand the CRBN neosubstrate landscape using a target-agnostic d... read more 

Neurotox: Deep learning decodes conserved hallmarks of neurotoxicity across venomous species

bioRxiv
Neurotoxic proteins drive the most pathophysiological effects of animal envenomation, yet it remains unclear whether neurotoxicity is encoded directly within the protein sequence or emerges from higher-order structure binding and interactions with th... read more 

NeuroNarrator: A Generalist EEG-to-Text Foundation Model for Clinical Interpretation via Spectro-Spatial Grounding and Temporal State-Space Reasoning

bioRxiv
Electroencephalography (EEG) provides a non-invasive window into neural dynamics at high temporal resolution and plays a pivotal role in clinical neuroscience research. Despite this potential, prevailing computational approaches to EEG analysis remai... read more 

Dual reinforcement-learning network modules for modeling decision-making with multiple strategies

bioRxiv
Animals and humans use multiple behavioral strategies to perform tasks. However, neural implementations of multiple strategies remain elusive, as some studies propose distinct pathways, while others observe overlapping brain regions associated with s... read more 

From General-Purpose to Disease-Specific Features: Aligning LLM Embeddings on a Disease-Specific Biomedical Knowledge Graph for Drug Repurposing

bioRxiv
Identifying new therapeutic uses for existing drugs is a major challenge in biomedicine, especially for complex neurodegenerative conditions such as Alzheimer disease and related dementias (ADRD), where treatment options remain limited and relevant d... read more 

Bacterial proteome foundation model enhances functional prediction from enzymes to ecological interactions

bioRxiv
Bacteria play fundamental roles in ecosystems, human health, and biotechnology. Although bacterial genome sequencing data have accumulated rapidly over the past decade, the metabolic and ecological functions of most sequenced bacteria remain poorly u... read more 

Improving Causal Gene Identification Using Large Language Models

bioRxiv
Genome-Wide Association Studies (GWAS) have successfully identified numerous loci associated with complex traits and diseases, yet pinpointing causal genes remains a significant challenge. The reliance on simple proximity-based heuristics is often in... read more 

A Universal, AI-based Design Framework for Efficient Manufacturing of mRNA Therapeutics

bioRxiv
The growth of mRNA therapeutics is limited by bespoke manufacturing processes. To overcome this barrier to access and innovation, we introduce an AI-driven framework that decouples sequence design from manufacturing, analogous to the universal design... read more 

Improving Turnaround Times with Artificial Intelligence in Microbiology

bioRxiv
This dual-center study evaluated the impact of artificial intelligence (AI) on urine culture turnaround times in Canadian diagnostic laboratories employing full microbiology laboratory automation. Data were collected before and after the implementati... read more