Dyslipidemia

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease

\textbf{Objective:} Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as Mild Cognitive Impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture structural and functional modulations of brain structure and function relying on multimodal MRI data and Single Nucleotide Polymor...

DeLIVR: a deep learning approach to IV regression for testing nonlinear causal effects in transcriptome-wide association studies.

Transcriptome-wide association studies (TWAS) have been increasingly applied to identify (putative) causal genes for complex traits and diseases. TWAS can be regarded as a two-sample two-stage least squares method for instrumental variable (IV) regression for causal inference. The standard TWAS (called TWAS-L) only considers a linear relationship between a gene's expression and a trait in stage 2,...

Comparison of machine learning models to predict complications of bariatric surgery: A systematic review.

Due to changes in lifestyle, bariatric surgery is expanding worldwide. However, this surgery has numerous complications, and early identification of ...

Deep Learning Models for Coronary Atherosclerosis Detection in Coronary CT Angiography.

BACKGROUND: Patients with atherosclerosis have a rather high risk of showing complications, if not diagnosed quickly and efficiently.

AI: A New Solution for Old Issues of Carotid Atherosclerotic Plaque.

A Novel Detection of Cerebrovascular Disease using Multimodal Medical Image Fusion.

BACKGROUND: Diseases are medical situations that are allied with specific signs and symptoms. A disease may be instigated by internal dysfunction or e...

H2Opred: a robust and efficient hybrid deep learning model for predicting 2'-O-methylation sites in human RNA.

2'-O-methylation (2OM) is the most common post-transcriptional modification of RNA. It plays a crucial role in RNA splicing, RNA stability and innate ...

DETERMINATION OF THE PRA POSITIVITY PERCENTAGE IN MALE PATIENTS WITH CHRONIC KIDNEY DISEASE BY USING FLOW CYTOMETRY TECHNIQUE.

The antibodies directed against human leukocyte antigen (HLA) molecules, which play a crucial role in allograft histocompatibility, are called anti-HL...

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

Automated detection of atrial fibrillation (AF) from electrocardiogram (ECG) traces remains a challenging task and is crucial for telemonitoring of pa...

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 illegal timber trade. Robust wood identification tool...

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 resection for rectal cancer. The ports were placed a...

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 low-density lipoprotein cholesterol (LDL-C) estimati...

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 world. Atherosclerosis is an asymptomatic condition th...

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 elucidated. This study aimed to assess long-term rena...

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 accurate assessment of coronary artery disease burden an...

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

OBJECTIVE: Low-density lipoprotein cholesterol (LDL-C) can be estimated using the Friedewald and Martin-Hopkins formulas. We developed LDL-C predictio...

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 difference between atherosclerotic vascular disease pr...

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 predictor of atherosclerotic coronary disease; however...

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. The occurrence of cardiovascular events is the ma...