Artificial Intelligence Medical Compendium

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

Showing 53,931 to 53,940 of 225,930 articles

SCOPE: AI-Assisted Early Detection of Potentially Curable Pancreatic Neoplasms on CT from Local and Global Information

medRxiv
Purpose: To develop SCOPE (Small-lesion COntextual Pancreatic Evaluator), a deep learning model designed to improve CT detection of small pancreatic lesions-pancreatic ductal adenocarcinoma (PDAC), pancreatic neuroendocrine tumors (PanNETs), and cyst... read more 

Predictive Modeling of COVID-19 Variant Peak Prevalence and Duration Using GISAID Data Across 15 Countries

medRxiv
BackgroundRapid emergence and replacement of SARS-CoV-2 variants underscore the need for early and reliable indicators of variant dominance to guide timely public health response. However, early genomic trajectories are typically short, sparse, and n... read more 

Uncertainty-aware personalized estimation of Parkinsons disease severity from longitudinal speech

medRxiv
Parkinsons disease is a progressive neurological disorder characterized by motor impairments whose severity is commonly assessed using the Unified Parkinsons Disease Rating Scale (UPDRS). Although clinically established, UPDRS assessment requires in-... read more 

Drug Safety Agents Using Graphs and Ontologies

medRxiv
In pharmacovigilance, analyzing drug safety cases is often time consuming due to the abundance of laboratory data, complex medical histories, and intricate temporal relationships. Agentic AI systems can significantly reduce case processing time by as... read more 

Using Artificial Intelligence to optimize agreement between interstitial sensors and capillary puncture in glycemic assessment and classification

medRxiv
Introduction: Blood glucose monitoring is essential for the management of diabetes mellitus. Continuous interstitial glucose (IG) monitoring systems are less invasive than capillary blood glucose (BG) measurements, but their agreement decreases at hi... 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 

Scalp microbiome differences in subjects with self-reported hair loss: A quantitative approach to microbial dysbiosis

bioRxiv
Objective: Hair loss is a common issue that affects a large proportion of the population, leading to lower self-confidence and quality of life. Microbial dysbiosis of the scalp has been shown to be associated with several different disorders leading ... 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