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Longitudinal biomarker data and health outcomes are routinely collected in many studies to assess how biomarker trajectories predict health outcomes. Existing methods primarily focus on mean biomarker profiles, treating variability as a…

Motivated by recent findings that within-subject (WS) visit-to-visit variabilities of longitudinal biomarkers can be strong risk factors for health outcomes, this paper introduces and examines a new joint model of a longitudinal biomarker…

The World Health Organization defines cardio-vascular disease (CVD) as "a group of disorders of the heart and blood vessels," including coronary heart disease and stroke (WHO 21). CVD is affected by "intermediate risk factors" such as…

Machine Learning · Computer Science 2023-05-04 Harish Chauhan , Nikunj Gupta , Zoe Haskell-Craig

Cardiovascular disease (CVDs) is a rapidly rising global concern due to unhealthy diets, lack of physical activity, and other factors. According to the World Health Organization (WHO), primary risk factors include elevated blood pressure,…

Artificial Intelligence · Computer Science 2024-09-25 Shashi Shekhar Kumar , Anurag Harsh , Ritesh Chandra , Sonali Agarwal

Objective: The study aimed to determine the prevalence of several non-communicable diseases (NCD) and analyze risk factors among adult patients seeking nutritional guidance in Dhaka, Bangladesh. Result: Our study observed the relationships…

Quantitative Methods · Quantitative Biology 2023-05-19 Mrinmoy Roy , Anica Tasnim Protity , Srabonti Das , Porarthi Dhar

The clinical and economic burden of cardiovascular diseases (CVDs) poses a global challenge. Growing evidence suggests an early assessment of arterial stiffness can provide insights into the pathogenesis of CVDs. However, it remains…

Medical Physics · Physics 2020-12-07 Guo-Yang Li , Yuxuan Jiang , Yang Zheng , Weiqiang Xu , Zhaoyi Zhang , Yanping Cao

The point of care services and medication have become simpler with efficient consumer electronics devices in a smart healthcare system. Cardiovascular disease is a critical illness which causes heart failure, and early and prompt…

Computers and Society · Computer Science 2022-12-16 Nidhi Sinha , Teena Jangid , Amit M. Joshi , Saraju P. Mohanty

Diabetes is a serious chronic metabolic disease. In the recent years, more and more consumer technology enterprises focusing on human health are committed to implementing accurate and non-invasive blood glucose algorithm in their products.…

Machine Learning · Computer Science 2025-03-05 Yiting Wei , Bingo Wing-Kuen Ling , Qing Liu , Jiaxin Liu

Purpose: Although elevated BMI is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that detailed body composition may uncover abdominal phenotypes of type 2…

Guidelines for the management of atherosclerotic cardiovascular disease (ASCVD) recommend the use of risk stratification models to identify patients most likely to benefit from cholesterol-lowering and other therapies. These models have…

Machine Learning · Computer Science 2019-06-17 Stephen Pfohl , Ben Marafino , Adrien Coulet , Fatima Rodriguez , Latha Palaniappan , Nigam H. Shah

Aging is a multidimensional process where phenotypes change at varying rates. Longitudinal studies of aging typically involve following a cohort of individuals over the course of several years. This design is hindered by cost, attrition,…

This project intends to study a cardiovascular disease risk early warning model based on one-dimensional convolutional neural networks. First, the missing values of 13 physiological and symptom indicators such as patient age, blood glucose,…

Machine Learning · Computer Science 2024-06-14 Yuxiang Hu , Jinxin Hu , Ting Xu , Bo Zhang , Jiajie Yuan , Haozhang Deng

Cardiovascular diseases (CVDs) encompass a group of disorders affecting the heart and blood vessels, including conditions such as coronary artery disease, heart failure, stroke, and hypertension. In cardiovascular diseases, heart failure is…

Artificial Intelligence · Computer Science 2024-07-12 Ershadul Haque , Manoranjan Paul , Faranak Tohidi

This study aimed to develop a machine learning (ML) algorithm capable of determining cardiovascular risk in multimodal retinal images from patients with type 1 diabetes mellitus, distinguishing between moderate, high, and very high-risk…

Traditionally, medical discoveries are made by observing associations and then designing experiments to test these hypotheses. However, observing and quantifying associations in images can be difficult because of the wide variety of…

Computer Vision and Pattern Recognition · Computer Science 2020-06-19 Ryan Poplin , Avinash V. Varadarajan , Katy Blumer , Yun Liu , Michael V. McConnell , Greg S. Corrado , Lily Peng , Dale R. Webster

Chronic diseases are long-lasting conditions that require lifelong medical attention. Using big EMR data, we have developed early disease risk prediction models for five common chronic diseases: diabetes, hypertension, CKD, COPD, and…

Machine Learning · Computer Science 2026-03-13 Shaheer Ahmad Khan , Muhammad Usamah Shahid , Muddassar Farooq

Background: Recent studies have used basic epicardial adipose tissue (EAT) assessments (e.g., volume and mean HU) to predict risk of atherosclerosis-related, major adverse cardiovascular events (MACE). Objectives: Create novel, hand-crafted…

Quantitative Methods · Quantitative Biology 2024-01-31 Tao Hu , Joshua Freeze , Prerna Singh , Justin Kim , Yingnan Song , Hao Wu , Juhwan Lee , Sadeer Al-Kindi , Sanjay Rajagopalan , David L. Wilson , Ammar Hoori

Background: Multiple medical and non-medical stressors, along with the complicity of their exposure pathways, have posted significant challenges to the epidemiological interpretation of the non-communicable diseases, including…

Applications · Statistics 2025-03-07 Jiangling Liu , Ya Liu , Banyun Zheng , Longjian Liu , Heqing Shen

Type 2 diabetes mellitus represents a prevalent and widespread global health concern, necessitating a comprehensive assessment of its risk factors. This study aimed towards learning whether there is any differential impact of age,…

We study the Heart Rate Variability (HRV) using scale specific variance and scaling exponents as measures of healthy and cardiac impaired individuals. Our results show that the variance and the scaling exponent are uncorrelated. We find…