Artificial Intelligence Medical Compendium

Machine Learning (ML) techniques have enabled the advancement of many technologies throughout the pharmaceutical industry, especially for drug discovery. One of the most rapidly growing technologies within the pharmaceutical space is gene therapy, wi... read more 

Breast cancer heterogeneity stems from diverse molecular alterations, including proteostasis loss due to chaperone system dysfunction. However, the impact of impaired chaperone activity on proteomic changes and tumorigenesis remains unclear. Here, ch... read more 

BACKGROUND: Colistin resistance in Acinetobacter baumannii (AB) is a serious clinical concern. This study aimed to identify resistance-related genes and assess their effects on resistance, growth, and pathogenicity. METHODS: Bioinformatics combined w... read more 

OBJECTIVE: To evaluate the comparative performance of a deep learning-reconstructed T1-weighted volumetric interpolated breath-hold examination (DL VIBE) on hepatobiliary phase MRI against the conventional T1 VIBE in biliary tree visualization, lesio... read more 

INTRODUCTION: The frailty index is widely used to identify vulnerable individuals at risk of adverse outcomes like mortality. However, its predictive performance compared to other mortality prediction models, especially in subpopulations like people ... read more 

Carrageenan (CG), a sulfated galactan derived from red seaweed, has emerged as a versatile biopolymer for developing sustainable, smart, and multifunctional biomaterials. This review critically surveys recent advances in CG bio(nano)composites, empha... read more 

Spatially varying regularization accommodates the deformation variations that may be necessary for different anatomical regions during deformable image registration. Historically, optimization-based registration models have harnessed spatially varyin... read more 

PURPOSE OF REVIEW: To discuss recent advances in imaging of the structural organization and functional connectivity of central vestibular disorders with various MRI techniques. Vestibular paroxysmia, in particular the characteristics of neurovascular... read more 

AIM: Neuropathic pain occurs commonly after stroke and represents a major source of disability for affected patients. This study aims to develop an accurate and computationally efficient framework for multi-level neuropathic pain detection using elec... read more 

Graph Neural Networks (GNNs) have become a powerful tool for modeling complex graph-structured data, achieving remarkable success in various graph mining tasks. However, many GNNs are limited to shallow architectures due to over-smoothing, which prev... read more