Dyslipidemia

Assessing the Generalizability of a Deep Learning-based Automated Atrial Fibrillation Algorithm.

Automated detection of atrial fibrillation (AF) from electrocardiogram (ECG) traces remains a challe...

SmartWoodID-an image collection of large end-grain surfaces to support wood identification systems.

Wood identification is a key step in the enforcement of laws and regulations aimed at combatting ill...

Using artificial intelligence to study atherosclerosis, predict risk and guide treatments in clinical practice.

[Eight mm Port-Site Hernia Following Robot-Assisted Abdominoperineal Resection for Rectal Cancer-A Case Report].

A 70s woman with a history of asthma and dyslipidemia underwent a robot-assisted abdominoperineal re...

Prospective Validation of a Machine Learning Model for Low-Density Lipoprotein Cholesterol Estimation.

OBJECTIVE: We aim to prospectively validate a previously developed machine learning algorithm for lo...

Rapid lipid-laden plaque identification in intravascular optical coherence tomography imaging based on time-series deep learning.

SIGNIFICANCE: Coronary heart disease has the highest rate of death and morbidity in the Western worl...

Influence of Robot-Assisted Partial Nephrectomy on Long-Term Renal Function as Assessed Using 99m-Tc DTPA Renal Scintigraphy.

The long-term split renal function after robot-assisted partial nephrectomy (RAPN) is yet to be elu...

Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study.

BACKGROUND: Atherosclerotic plaque quantification from coronary CT angiography (CCTA) enables accura...

Estimation of Low-Density Lipoprotein Cholesterol Concentration Using Machine Learning.

OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Mar...

Elevated Coronary Artery Calcium Quantified by a Validated Deep Learning Model From Lung Cancer Radiotherapy Planning Scans Predicts Mortality.

PURPOSE: Coronary artery calcium (CAC) quantified on computed tomography (CT) scans is a robust pred...

Detecting Racial/Ethnic Health Disparities Using Deep Learning From Frontal Chest Radiography.

PURPOSE: The aim of this study was to assess racial/ethnic and socioeconomic disparities in the diff...

Correlation among cystatin C, homocysteine and arteriosclerosis indexes in patients with chronic kidney disease.

OBJECTIVES: Chronic kidney disease (CKD) has become an important public health problem in the world....

Automatic Deep Learning Segmentation and Quantification of Epicardial Adipose Tissue in Non-Contrast Cardiac CT scans.

An Automatic deep learning semantic segmentation (ADLS) using DeepLab-v3-plus technique is proposed ...

Stratification of carotid atheromatous plaque using interpretable deep learning methods on B-mode ultrasound images.

Carotid atherosclerosis is the major cause of ischemic stroke resulting in significant rates of mort...

Improved Centerline Extraction in Fully Automated Coronary Ostium Localization and Centerline Extraction Framework using Deep Learning.

Coronary artery extraction in cardiac CT angiography (CCTA) image volume is a necessary step for any...

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence.

OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque charact...

Improving the accuracy and convergence of drug permeation simulations via machine-learned collective variables.

Understanding the permeation of biomolecules through cellular membranes is critical for many biotech...

Joint Associations of Multiple Dietary Components With Cardiovascular Disease Risk: A Machine-Learning Approach.

The human diet consists of a complex mixture of components. To realistically assess dietary impacts ...

[Robot-assisted single-anastomosis duodeno-ileal bypass with sleeve gastrectomy].

Single-anastomosis duodeno-ileal bypass with sleeve gastrectomy (SADI-S) is simpler and has similar ...

Verification and comparison of three prediction models of ischemic stroke in young adults based on the back propagation neural networks.

This work aims to explore risk factors for ischemic stroke in young adults and analyze the Tradition...

Generative models for predicting chemical composition of gallstones.

OBJECTIVE: As we know, gallstones are a gallbladder disease with high incidence around the world. As...