Artificial Intelligence Medical Compendium

Multivariate workload prediction in cloud computing environments is a critical research problem. Effectively capturing inter-variable correlations and temporal patterns in multivariate time series is key to addressing this challenge. To address this ... read more 

Generative Adversarial Networks (GANs) have demonstrated remarkable success in high-quality image synthesis, with StyleGAN and its successor, StyleGAN2, achieving state-of-the-art performance in terms of realism and control over generated features. H... read more 

Abdominal aortic aneurysm (AAA) is a progressive and life-threatening vascular disorder characterized by abnormal dilation of the abdominal aorta and a high risk of rupture. Current pharmacological interventions remain limited in efficacy, highlighti... read more 

Although graph neural networks (GNNs) have proven powerful in molecular property prediction tasks, they tend to underperform when trained on small datasets. Conventional data augmentation strategies are generally ineffective in this context, as simpl... read more 

This study proposes a novel methodology to develop and manage data-driven models for ship machinery Prognostics and Health Management (PHM). A four-stroke marine engine is investigated considering exhaust valve wear degradation. Simulated datasets ar... read more 

Achieving temporal consistency in video content poses a significant challenge for high-quality video styling. Unfortunately, current video style transfer techniques often amplify the differences between frames in the input video, leading to unsmooth ... read more 

PURPOSE: Artificial Intelligence (AI) is increasingly recognized for its potential in improving the detection, classification, prediction, and segmentation of colon cancer. Yet, the reliability of these applications depends on the quality and complet... read more 

PURPOSE: Landiolol is a beta-blocker used in the treatment of Sepsis. However, how this drug influences key genes and pathways involved in disease remains unknown. This study aimed to explore potential biomarkers involved in the mechanism of Landiolo... read more 

Aspect-based sentiment analysis enables precise identification of sentiment-bearing entities and attributes in textual content, thereby delivering granular sentiment information for downstream applications. Recent research has focused on enhancing se... read more 

PURPOSE: To evaluate the predictive performance of a clinical-CT-radiomics nomogram based on radiomics signature and independent clinical-CT predictors for predicting endoscopic red color sign (RC) in cirrhotic patients with esophageal varices (EV). ... read more