Dyslipidemia

Fibroblast growth factor 5: a novel biomarker for familial hypercholesterolaemia.

BACKGROUND AND AIMS: Identification of individuals affected by familial hypercholesterolaemia (FH) is suboptimal when genetic tests are unavailable. Relying only on low-density lipoprotein cholesterol (LDL-C) is challenging as it may not allow distinguishing individuals with FH from hypercholesterolaemic (HC) individuals from the general population. The aim of this study was to determine whether b...

Predicting overactive bladder from inflammatory markers: A machine learning approach using NHANES 2005-2020.

Overactive bladder (OAB), a prevalent condition characterized by urgency and nocturia, imposes significant burdens on both quality of life and healthcare systems. Emerging evidence implicates systemic inflammation in OAB pathogenesis; however, the role of complete blood count (CBC)-derived inflammatory biomarkers remains underexplored. This cross-sectional study analyzed data from 35,394 participa...

Integrating Natural Language Processing and Exercise Monitoring for Early Diagnosis of Metabolic Syndrome: A Deep Learning Approach

Metabolic syndrome (MetS) is a medication condition characterized by abdominal obesity, insulin resistance, hypertension and hyperlipidemia. It incr...

Acute coronary syndromes: mechanisms, challenges, and new opportunities.

Despite advances in research and patient management, atherosclerosis and its dreaded acute and chronic sequelae continue to account for one out of thr...

Machine-Learning Assisted Screening with FIND FH for Familial Hypercholesterolemia among Youth.

Although the American Academy of Pediatrics recommends universal lipid screening among children to find cases of familial hypercholesterolemia, such s...

Combined assessment of stress hyperglycemia ratio and glycemic variability to predict all-cause mortality in critically ill patients with atherosclerotic cardiovascular diseases across different glucose metabolic states: an observational cohort study with machine learning.

BACKGROUND: Stress hyperglycemia ratio (SHR) and glycemic variability (GV) reflect acute glucose elevation and fluctuations, which correlate with adve...

Eliciting the Impact of Metformin and Statins on Prostate Cancer Outcomes from a Real-life National Database Analysis.

Several large analyses have revealed contradictory results regarding the association between prostate cancer (PC) survival and the use of statins pres...

Predicting peripartum depression using elastic net regression and machine learning: the role of remnant cholesterol.

BACKGROUND: Traditional statistical methods have dominated research on peripartum depression (PPD), but innovative approaches may provide deeper insig...

Identification of Novel Diagnostic Markers for Atherosclerosis Using Machine-Learning Algorithms.

OBJECTIVE: To outline immune-cell infiltration and identify diagnostic genes for atherosclerosis (AS) to better understand the potential molecular pro...

Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including dia...

[Coronary computed tomography in the clinical arena. Recent evidence and future perspectives].

In the past few years, computed tomography coronary angiography (CTCA) has rapidly become a widely used diagnostic tool in several clinical settings a...

Expert consensus document on artificial intelligence of the Italian Society of Cardiology.

Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been us...

A Two-Stage Interpretable Matching Framework for Causal Inference

Matching in causal inference from observational data aims to construct treatment and control groups with similar distributions of covariates, thereb...

SydneyScapes: Image Segmentation for Australian Environments

Autonomous Vehicles (AVs) are being partially deployed and tested across various global locations, including China, the USA, Germany, France, Japan,...

Predicting Prostate Cancer Diagnosis Using Machine Learning Analysis of Healthcare Utilization Patterns.

This study investigated healthcare utilization patterns prior to prostate cancer diagnoses, aiming to develop machine learning models for early predic...

CardioTabNet: A Novel Hybrid Transformer Model for Heart Disease Prediction using Tabular Medical Data

The early detection and prediction of cardiovascular diseases are crucial for reducing the severe morbidity and mortality associated with these cond...

A Causality-Inspired Model for Intima-Media Thickening Assessment in Ultrasound Videos

Carotid atherosclerosis represents a significant health risk, with its early diagnosis primarily dependent on ultrasound-based assessments of caroti...

ImplicitCell: Resolution Cell Modeling of Joint Implicit Volume Reconstruction and Pose Refinement in Freehand 3D Ultrasound

Freehand 3D ultrasound enables volumetric imaging by tracking a conventional ultrasound probe during freehand scanning, offering enriched spatial in...

A Deep Learning Model for Three-Dimensional Determination of Whole Thoracic Vertebral Bone Mineral Density from Noncontrast Chest CT: The Multi-Ethnic Study of Atherosclerosis.

Background Recent studies have investigated how deep learning (DL) algorithms applied to CT using two-dimensional (2D) segmentation (sagittal or axial...

Machine Learning Framework for Early Power, Performance, and Area Estimation of RTL

A critical stage in the evolving landscape of VLSI design is the design phase that is transformed into register-transfer level (RTL), which specifie...