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In recent years, ML algorithms have been shown to be useful for predicting diseases based on health data and posed a potential application area for these algorithms such as modeling of diseases. The majority of these applications employ…

Machine Learning · Computer Science 2024-12-24 Elham Musaaed , Nabil Hewahi , Abdulla Alasaadi

Stress, anxiety, and nervousness are all high-risk health states in everyday life. Previously, stress levels were determined by speaking with people and gaining insight into what they had experienced recently or in the past. Typically,…

Signal Processing · Electrical Eng. & Systems 2022-04-08 Sadhana Tiwari , Sonali Agarwal

Kidneys are the filter of the human body. About 10% of the global population is thought to be affected by Chronic Kidney Disease (CKD), which causes kidney function to decline. To protect in danger patients from additional kidney damage,…

The primary aim of this paper is to comprehend, assess, and analyze the role, relevance, and efficiency of machine learning models in predicting heart disease risks using clinical data. While the importance of heart disease risk prediction…

Machine Learning · Computer Science 2024-10-22 Balaji Shesharao Ingole , Vishnu Ramineni , Nikhil Bangad , Koushik Kumar Ganeeb , Priyankkumar Patel

Diet plays a crucial role in health, and understanding the causal effects of dietary patterns is essential for informing public health policy and personalized nutrition strategies. However, causal inference in nutritional epidemiology faces…

Methodology · Statistics 2026-01-26 Dafne Zorzetto , Zizhao Xie , Julian Stamp , Arman Oganisian , Roberta De Vito

Cardiovascular disease remains a leading global cause of mortality, necessitating accurate risk prediction tools. Traditional methods, such as QRISK and the Framingham heart score, exhibit limitations in their ability to incorporate…

Genomics · Quantitative Biology 2024-02-12 Farnoush Shishehbori , Zainab Awan

Worldwide research shows that millions of lives lost per year because of heart disease. The healthcare sector produces massive volumes of data on heart disease that are sadly not used to locate secret knowledge for successful decision…

Machine Learning · Computer Science 2021-01-05 Md. Touhidul Islam , Sanjida Reza Rafa , Md. Golam Kibria

Cardiovascular disease and chronic kidney disease are major complications of diabetes, leading to high morbidity and mortality. Early detection of these conditions is critical, yet traditional diagnostic markers often lack sensitivity in…

Other Quantitative Biology · Quantitative Biology 2025-10-20 Syed Ibad Hasnain

Most people around the globe are dying due to heart disease. The main reason behind the rapid increase in the death rate due to heart disease is that there is no infrastructure developed for the healthcare department that can provide a…

Machine Learning · Computer Science 2023-06-06 Muhammad Shoaib Farooq , Kiran Amjad

The detection of cardiovascular diseases (CVD) using machine learning techniques represents a significant advancement in medical diagnostics, aiming to enhance early detection, accuracy, and efficiency. This study explores a comparative…

Machine Learning · Computer Science 2024-05-28 Dayana K , S. Nandini , Sanjjushri Varshini R

Chronic Obstructive Pulmonary Disease (COPD) is an irreversible airway obstruction with a high societal burden. Although smoking is known to be the biggest risk factor, additional components need to be considered. In this study, we aim to…

Quantitative Methods · Quantitative Biology 2023-02-08 Soojin Lee , Ingu Sean Lee , Samuel Kim

The burden of diabetes has disproportionately impacted Hispanic/Latino residents in the United States, with diet recognized as a major modifiable risk factor. Outcome-dependent dietary patterns provide insight into what foods may be…

Early disease detection and prevention methods based on effective interventions are gaining attention. Machine learning technology has enabled precise disease prediction by capturing individual differences in multivariate data. Progress in…

Globally, Coronary Heart Disease (CHD) is one of the main causes of death. Early detection of CHD can improve patient outcomes and reduce mortality rates. We propose a novel framework for predicting the presence of CHD using a combination…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 R. Selvaraj , T. Satheesh , V. Suresh , V. Yathavaraj

Heart disease is a serious global health issue that claims millions of lives every year. Early detection and precise prediction are critical to the prevention and successful treatment of heart related issues. A lot of research utilizes…

Machine Learning · Computer Science 2024-07-30 Rahul Karmakar , Udita Ghosh , Arpita Pal , Sattwiki Dey , Debraj Malik , Priyabrata Sain

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 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

Health risks from cigarette smoking -- the leading cause of preventable death in the United States -- can be substantially reduced by quitting. Although most smokers are motivated to quit, the majority of quit attempts fail. A number of…

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

This study analyzes patterns of physical, mental, lifestyle, and personality factors in college students in different periods over the course of a semester and models their relationships with students' academic performance. The data…