Dyslipidemia

Optimized Machine Learning for the Early Detection of Polycystic Ovary Syndrome in Women.

Polycystic ovary syndrome (PCOS) is a medical condition that impacts millions of women worldwide; however, due to a lack of public awareness, as well as the expensive testing involved in the identification of PCOS, 70% of cases go undiagnosed. Therefore, the primary objective of this study is to design an expert machine learning (ML) model for the early diagnosis of PCOS based on initial symptoms ...

An efficient approach on risk factor prediction related to cardiovascular disease around Kumbakonam, Tamil Nadu, India, using unsupervised machine learning techniques.

Nowadays, human beings suffer from varieties of diseases due to the environmental circumstances and their residing habits. Cardiovascular diseases (CVD) are the leading cause of mortality among all diseases. CVDs are heart-related diseases. In early days, the lack of technological advancements resulted in the loss of many human lives. That is, delay in diagnosis resulted in delay in treatments, wh...

Functionally characterizing obesity-susceptibility genes using CRISPR/Cas9, in vivo imaging and deep learning.

Hundreds of loci have been robustly associated with obesity-related traits, but functional characterization of candidate genes remains a bottleneck. A...

Predicting low density lipoprotein cholesterol target attainment using machine learning in patients with coronary artery disease receiving moderate-dose statin therapy.

Low-density lipoprotein cholesterol (LDL-C) is an important factor in the development of cardiovascular disease, making its management a key aspect of...

Predicting Type 2 diabetes onset age using machine learning: A case study in KSA.

The rising prevalence of Type 2 Diabetes (T2D) in Saudi Arabia presents significant healthcare challenges. Estimating the age at onset of T2D can aid ...

Discovering Vitamin-D-Deficiency-Associated Factors in Korean Adults Using KNHANES Data Based on an Integrated Analysis of Machine Learning and Statistical Techniques.

: Vitamin D deficiency (VDD) is a global health concern associated with metabolic disease and immune dysfunction. Despite known risk factors like limi...

TQGDNet: Coronary artery calcium deposit detection on computed tomography.

Coronary artery disease (CAD) continues to be a leading global cause of cardiovascular related mortality. The scoring of coronary artery calcium (CAC)...

Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, usin...

Prediction of the Risk of Adverse Clinical Outcomes with Machine Learning Techniques in Patients with Noncommunicable Diseases.

Decision-making in chronic diseases guided by clinical decision support systems that use models including multiple variables based on artificial intel...

Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.

Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical to...

Machine Learning Analysis of Nutrient Associations with Peripheral Arterial Disease: Insights from NHANES 1999-2004.

BACKGROUND: Peripheral arterial disease (PAD) is a common manifestation of atherosclerosis, affecting over 200 million people worldwide. The incidence...

The triglyceride-glucose index and its obesity-related derivatives as predictors of all-cause and cardiovascular mortality in hypertensive patients: insights from NHANES data with machine learning analysis.

BACKGROUND: Hypertension (HTN) is a global public health concern and a major risk factor for cardiovascular disease (CVD) and mortality. Insulin resis...

Exploring the role of oxidative stress in carotid atherosclerosis: insights from transcriptomic data and single-cell sequencing combined with machine learning.

BACKGROUND: Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative str...

Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study.

BACKGROUND: With the rising diagnostic rate of gallbladder polypoid lesions (GPLs), differentiating benign cholesterol polyps from gallbladder adenoma...

A comprehensive analysis of stroke risk factors and development of a predictive model using machine learning approaches.

Stroke is a leading cause of death and disability globally, particularly in China. Identifying risk factors for stroke at an early stage is critical t...

A cohort study of serum 25-hydroxyvitamin D levels and the risk of hyperlipidaemia in adults.

OBJECTIVE: This study aims to investigate the potential association between serum 25(OH)D levels and the risk of hyperlipidemia in adults through a pr...

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 ca...

Development and validation of machine-learning models for predicting the risk of hypertriglyceridemia in critically ill patients receiving propofol sedation using retrospective data: a protocol.

INTRODUCTION: Propofol is a widely used sedative-hypnotic agent for critically ill patients requiring invasive mechanical ventilation (IMV). Despite i...

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-chemothera...

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...