Atherosclerosis

Machine Learning Algorithms to Predict the Risk of Rupture of Intracranial Aneurysms: a Systematic Review.

PURPOSE: Subarachnoid haemorrhage is a potentially fatal consequence of intracranial aneurysm rupture, however, it is difficult to predict if aneurysms will rupture. Prophylactic treatment of an intracranial aneurysm also involves risk, hence identifying rupture-prone aneurysms is of substantial clinical importance. This systematic review aims to evaluate the performance of machine learning algori...

Large Scale Ultrafast Manufacturing of Wireless Soft Bioelectronics Enabled by Autonomous Robot Arm Printing Assisted by a Computer Vision-Enabled Guidance System for Personalized Wound Healing.

A Customized wound patch for Advanced tissue Regeneration with Electric field (CARE), featuring an autonomous robot arm printing system guided by a computer vision-enabled guidance system for fast image recognition is introduced. CARE addresses the growing demand for flexible, stretchable, and wireless adhesive bioelectronics tailored for electrotherapy, which is suitable for rapid adaptation to i...

Artificial intelligence modeling of biomarker-based physiological age: Impact on phase 1 drug-metabolizing enzyme phenotypes.

Age and aging are important predictors of health status, disease progression, drug kinetics, and effects. The purpose was to develop ensemble learning...

Machine learning-enhanced modeling and characterization for optimizing dietary Fiber production from Highland barley bran.

This study investigated the modification of highland barley bran through co-fermentation of Lactobacillus bulgaricus and Kluyveromyces marxianus, and ...

Improving arterial stiffness prediction with machine learning utilizing hemodynamics and biomechanical features derived from phase contrast magnetic resonance imaging.

Arterial stiffness has emerged as a prominent marker of risk for cardiovascular diseases. Few studies are interested in predicting symptomatic or asym...

Diagnostic and predictive value of radiomics-based machine learning for intracranial aneurysm rupture status: a systematic review and meta-analysis.

Currently, the growing interest in radiomics within the clinical practice has prompted some researchers to differentiate the rupture status of intracr...

Data augmentation via warping transforms for modeling natural variability in the corneal endothelium enhances semi-supervised segmentation.

Image segmentation of the corneal endothelium with deep convolutional neural networks (CNN) is challenging due to the scarcity of expert-annotated dat...

Circulating endothelial progenitor cells and inflammatory markers in type 1 diabetes after an acute session of aerobic exercise.

OBJECTIVE: To determine circulating endothelial progenitor cells (EPC) counts and levels of inflammatory markers in individuals with and without type ...

CAD-PsorNet: deep transfer learning for computer-assisted diagnosis of skin psoriasis.

Psoriasis, being a chronic, inflammatory, lifelong skin disorder, has become a major threat to the human population. The precise and effective diagnos...

HiDDEN: a machine learning method for detection of disease-relevant populations in case-control single-cell transcriptomics data.

In case-control single-cell RNA-seq studies, sample-level labels are transferred onto individual cells, labeling all case cells as affected, when in r...

Artificial Intelligence-Assisted Surgical Scene Recognition: A Comparative Study Among Health Care Professionals.

OBJECTIVE: To compare the ability of a deep-learning platform (the MACSSwin-T model) with health care professionals in detecting cerebral aneurysms fr...

ChatGPT Responses to Clinical Questions in the Japan Atherosclerosis Society Guidelines for Prevention of Atherosclerotic Cardiovascular Disease 2022.

AIMS: Artificial intelligence is increasingly used in the medical field. We assessed the accuracy and reproducibility of responses by ChatGPT to clini...

Adaptive FPGA-Based Accelerators for Human-Robot Interaction in Indoor Environments.

This study addresses the challenges of human-robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based acc...

Construction of the miRNA/Pyroptosis-Related Molecular Regulatory Axis in Abdominal Aortic Aneurysm: Evidence From Transcriptome Data Combined With Multiple Machine Learning Approaches Followed by Experiment Validation.

Abdominal aortic aneurysm (AAA) represents a permanent and localized widening of the abdominal aorta, posing a potentially lethal risk of aortic rupt...

Impact of nutrition-related laboratory tests on mortality of patients who are critically ill using artificial intelligence: A focus on trace elements, vitamins, and cholesterol.

BACKGROUND: This study aimed to understand the collective impact of trace elements, vitamins, cholesterol, and prealbumin on patient outcomes in the i...

Detection of carotid plaques on panoramic radiographs using deep learning.

OBJECTIVES: Panoramic radiographs (PRs) can reveal an incidental finding of atherosclerosis, or carotid artery calcification (CAC), in 3-15% of examin...

Predicting laboratory aspirin resistance in Chinese stroke patients using machine learning models by GP1BA polymorphism.

This study aims to use machine learning model to predict laboratory aspirin resistance (AR) in Chinese stroke patients by incorporating patient charac...

Deciphering the role of lipid metabolism-related genes in Alzheimer's disease: a machine learning approach integrating Traditional Chinese Medicine.

BACKGROUND: Alzheimer's disease (AD) represents a progressive neurodegenerative disorder characterized by the accumulation of misfolded amyloid beta p...

Enhancing Aortic Aneurysm Surveillance: Transformer Natural Language Processing for Flagging and Measuring in Radiology Reports.

BACKGROUND: Incidental findings of aortic aneurysms (AAs) often go unreported, and established patients are frequently lost to follow-up. Natural lang...

Identification of novel biomarkers for atherosclerosis using single-cell RNA sequencing and machine learning.

Atherosclerosis (AS) is a predominant etiological factor in numerous cardiovascular diseases, with its associated complications such as myocardial inf...