Artificial Intelligence Medical Compendium

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

Showing 53,551 to 53,560 of 225,548 articles

Hierarchical Representation Learning for Drug Mechanism-of-Action Prediction from Gene Expression Data

bioRxiv
Deciphering drug mechanisms of action (MoAs) from transcriptional responses is key for discovery and repurposing. While recent machine learning approaches improve prediction accuracy beyond traditional similarity metrics, they often lack biological s... read more 

ABFormer: A Transformer-based Model to Enhance Antibody-Drug Conjugates Activity Prediction through Contextualized Antibody-Antigen Embedding

bioRxiv
Computational screening is increasingly becoming a crucial aspect of Antibody Drug Conjugate (ADC) research, allowing the elimination of dead ends at earlier stages and concentrating on potential candidates, which can significantly reduce the cost of... read more 

Computational Convergence of Adaptive Immunity and Artificial Intelligence

bioRxiv
The adaptive immune system and modern artificial intelligence (AI) have independently converged on identical computational strategies for solving the recognition and generalization problem: learning to identify which inputs should be associated with ... read more 

Deconvolving mutation effects on protein stability and function with disentangled protein language models

bioRxiv
Understanding how evolutionary constraints shape protein sequences is fundamental to deciphering the molecular mechanisms underlying protein stability and function, which has broad implications in protein engineering and therapeutics development. Rec... read more 

A consensus spinal cord cell type atlas across mouse, macaque, and human

bioRxiv
The spinal cord contains evolutionarily conserved cell types critical for motor function, sensory processing, and autonomic regulation, many of which are implicated in diverse neurological diseases and injuries. Yet the field lacks a comprehensive mo... read more 

The Evolutionary Structure of Acoustic Learnability: A Deep Learning Approach to Neotropical Birdsong

bioRxiv
Passive Acoustic Monitoring offers a scalable solution for biodiversity assessment in the Neotropics, but classifying hundreds of sympatric species from complex soundscapes remains a major challenge. Here, we develop a deep learning framework for lar... read more 

NeuroConText: Contrastive Learning for Neuroscience Meta-Analysis with Rich Text Representation

bioRxiv
Brain meta-analysis is the common way to gather information about human brain function across the existing literature in order to formulate hypotheses and contextualize new findings. However, automated meta-analysis tools face challenges such as inco... read more 

Explainable Deep-Learning on condition specific expression profiles reveals critical cytosines in gene regulation

bioRxiv
Compared to other nucleotides, the cytosines stand as the most expressive one for gene regulation in plants due to its status as methylation-based epigenetic switch. Methylation of some of these cytosines may have higher impact on downstream genes, m... read more 

Intrinsic properties ensure reliable attractor dynamics in learned neural assemblies embedded within noisy, asynchronous networks

bioRxiv
Neural representations rely on the ability of neuronal assemblies to display organized spiking patterns, despite being embedded within noisy networks. These structured patterns arise from attractor dynamics due to activity reverberation promoted by l... read more 

Prediction of protein-carbohydrate binding sites from protein primary sequence

bioRxiv
Background: A protein is a large complex macromolecule that has a crucial role in performing most of the work in cells and tissues. It is made up of one or more long chains of amino acid residues. Another important biomolecule, after DNA and protein,... read more