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Metabolic Syndrome

Latest AI and machine learning research in metabolic syndrome for healthcare professionals.

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Impact of Mydriasis on Image Gradability and Automated Diabetic Retinopathy Screening with a Handheld Camera in Real-World Settings

Diabetic retinopathy (DR) screening in low- and middle-income countries (LMICs) faces challenges due...

Development and validation of a multivariable Prediction Model for Pre-diabetes and Diabetes using Easily Obtainable Clinical Data

In the US, pre-diabetes and diabetes are increasing in prevalence alongside other chronic diseases. ...

MUTATE: A Human Genetic Atlas of Multi-organ AI Endophenotypes using GWAS Summary Statistics

Artificial intelligence (AI) has been increasingly integrated into imaging genetics to provide inter...

Predicting mortality in critically ill patients with hypertension using machine learning and deep learning models

Accurate prediction of mortality in critically ill patients with hypertension admitted to the Intens...

Development and Application of Natural Language Processing on Unstructured Data in Hypertension: A Scoping Review

Hypertension is a global health concern with a vast body of unstructured data, such as clinical note...

Multi-organ metabolome biological age implicates cardiometabolic conditions and mortality risk

Biological aging clocks across organs and omics data, including clinical phenotypes, neuroimaging, p...

MRI-Derived Variables Combined with Machine Learning for Pulmonary Hypertension Risk Prediction: A Retrospective Analysis

Pulmonary hypertension (PH) is a severe and progressive vascular disease for which early diagnosis a...

Predicting 28-Day Mortality in First-Time ICU Patients with Heart Failure and Hypertension Using LightGBM: A MIMIC-IV Study

Heart Failure (HF) and Hypertension (HTN) are common yet severe cardiovascular conditions, both of w...

Real-World Type 2 Diabetes Second-Line Treatment Allocation Among Patients

This study aimed to evaluate the impact of socioeconomic disparities on the allocation of second-lin...

Clinical phenotypes in hypertension: a data-driven approach to risk stratification and outcome prediction

Hypertension (HTN) is a major contributor to cardiovascular (CV) morbidity and mortality. Its hetero...

Machine learning models for the prediction of COVID-19 prognosis in the primary health care setting

This study aimed to identify prognostic factors associated with poor outcomes of COVID-19 at diagnos...

Hypertension Screening via Awake-Sleep Differences in Photoplethysmogram Signals

Hypertension is a major risk factor for cardiovascular diseases. This study proposes a novel hyperte...

DeepDrug2: A Germline-focused Graph Neural Network Framework for Alzheimer’s Drug Repurposing Validated by Electronic Health Records

Alzheimer’s disease (AD) is a complex neurodegenerative disorder with limited therapeutic options. T...

Automated Deep Learning Pipeline for Characterizing Left Ventricular Diastolic Function

Left ventricular diastolic dysfunction (LVDD) is most commonly evaluated by echocardiography. Howeve...

Integrative Machine Learning Approach to Risk Prediction for Dementia and Alzheimer’s Disease

Dementia, especially Alzheimer’s disease (AD), is a major global health challenge marked by progress...

Target Trial Emulation Applications in Hypertension Research: A Scoping Review

Target Trial Emulation (TTE) has emerged as a rigorous framework for causal inference using observat...

Deep Learning-Based Risk Prediction Model for Major Adverse Cardiovascular Events in Long-Term Breast Cancer Survivors

Clinical practice guidelines recommend cardiovascular toxicity risk restratification including evalu...

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