Atherosclerosis

Random Survival Forest Machine Learning for the Prediction of Cardiovascular Events Among Patients With a Measured Lipoprotein(a) Level: A Model Development Study.

BACKGROUND: Established risk models may not be applicable to patients at higher cardiovascular risk with a measured Lp(a) (lipoprotein[a]) level, a causal risk factor for atherosclerotic cardiovascular disease.

Predicting doxorubicin-induced cardiotoxicity in breast cancer: leveraging machine learning with synthetic data.

Doxorubicin (DOXO) is a primary treatment for breast cancer but can cause cardiotoxicity in over 25% of patients within the first year post-chemotherapy. Recognizing at-risk patients before DOXO initiation offers pathways for alternative treatments or early protective actions. We analyzed data from 78 Brazilian breast cancer patients, with 34.6% developing cardiotoxicity within a year of their fin...

Sulfonic acid functionalized β-amyloid peptide aggregation inhibitors and antioxidant agents for the treatment of Alzheimer's disease: Combining machine learning, computational, in vitro and in vivo approaches.

Alzheimer's disease (AD) is characterized as a neurodegenerative disorder that is caused by plaque formation by accumulating β-amyloid (Aβ), leading t...

A machine learning-based model for predicting the risk of cognitive frailty in elderly patients on maintenance hemodialysis.

Elderly patients undergoing maintenance hemodialysis (MHD) face a heightened risk of cognitive frailty (CF), which significantly compromises quality o...

Advances in the Application of Artificial Intelligence in the Ultrasound Diagnosis of Vulnerable Carotid Atherosclerotic Plaque.

Vulnerable atherosclerotic plaque is a type of plaque that poses a significant risk of high mortality in patients with cardiovascular disease. Ultraso...

Integrative bioinformatics and machine learning approach unveils potential biomarkers linking coronary atherosclerosis and fatty acid metabolism-associated gene.

BACKGROUND: Atherosclerosis (AS) is increasingly recognized as a chronic inflammatory disease that significantly compromises vascular health and acts ...

Evaluating a clinically available artificial intelligence model for intracranial aneurysm detection: a multi-reader study and algorithmic audit.

PURPOSE: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracrania...

Patch-Wise Deep Learning Method for Intracranial Stenosis and Aneurysm Detection-the Tromsø Study.

Intracranial atherosclerotic stenosis (ICAS) and intracranial aneurysms are prevalent conditions in the cerebrovascular system. ICAS causes a narrowin...

Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging.

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecti...

Treatment of neovascular age-related macular degeneration: one year real-life results with intravitreal Brolucizumab.

BACKGROUND: Age-related macular degeneration (AMD) is a prevalent cause of irreversible vision loss worldwide, particularly among the elderly populati...

A deep learning model for carotid plaques detection based on CTA images: a two stepwise early-stage clinical validation study.

OBJECTIVE: To develop a deep learning (DL) model for carotid plaque detection based on CTA images and evaluate the clinical application feasibility an...

Early detection of canine hemangiosarcoma via cfDNA fragmentation and copy number alterations in liquid biopsies using machine learning.

Hemangiosarcoma is a highly malignant tumor commonly affecting canines, originating from endothelial cells that line blood vessels, underscoring the i...

Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment.

BACKGROUND: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variabil...

Prediction of Aneurysm Sac Shrinkage After Endovascular Aortic Repair Using Machine Learning-Based Decision Tree Analysis.

INTRODUCTION: A simple risk stratification model to predict aneurysm sac shrinkagein patients undergoing endovascular aortic repair (EVAR) for abdomin...

The role of endothelial cell-related gene COL1A1 in prostate cancer diagnosis and immunotherapy: insights from machine learning and single-cell analysis.

BACKGROUND: Endothelial cells are integral components of the tumor microenvironment and play a multifaceted role in tumor immunotherapy. Targeting end...

Construction of a poor prognosis prediction and visualization system for intracranial aneurysm endovascular intervention treatment based on an improved machine learning model.

OBJECTIVE: To evaluate the clinical utility of improved machine learning models in predicting poor prognosis following endovascular intervention for i...

Effects of feeding of vitamin C on embryonic development, hatching process, and chick rectal temperature of broiler embryos.

Maternal nutritional status plays a crucial role in embryonic development and has persistent effects on postnatal chicks. Vitamin C (VC) plays an impo...

Advanced AI-assisted panoramic radiograph analysis for periodontal prognostication and alveolar bone loss detection.

BACKGROUND: Periodontitis is a chronic inflammatory disease affecting the gingival tissues and supporting structures of the teeth, often leading to to...

Prediction of pulmonary embolism by an explainable machine learning approach in the real world.

In recent years, large amounts of researches showed that pulmonary embolism (PE) has become a common disease, and PE remains a clinical challenge beca...

Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.

Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (...