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Acute myocardial infarction (AMI) is one of the most severe manifestation of coronary artery disease. ST-segment elevation myocardial infarction (STEMI) is the most serious type of AMI. We proposed to develop a machine learning algorithm…

定量方法 · 定量生物学 2022-11-29 Ding Tao , Chen Liu , Shihan Wan

Most pregnancies and births result in a good outcome, but complications are not uncommon and when they do occur, they can be associated with serious implications for mothers and babies. Predictive modeling has the potential to improve…

Heart disease is a leading cause of premature death worldwide, particularly among middle-aged and older adults, with men experiencing a higher prevalence. According to the World Health Organization (WHO), non-communicable diseases,…

Cardiovascular disease, especially heart failure is one of the major health hazard issues of our time and is a leading cause of death worldwide. Advancement in data mining techniques using machine learning (ML) models is paving promising…

In today's world, a massive amount of data is available in almost every sector. This data has become an asset as we can use this enormous amount of data to find information. Mainly health care industry contains many data consisting of…

机器学习 · 计算机科学 2022-03-10 Hafsa Binte Kibria , Abdul Matin

Myocardial infarction (MI) is the leading cause of mortality and morbidity in the world. Early therapeutics of MI can ensure the prevention of further myocardial necrosis. Echocardiography is the fundamental imaging technique that can…

图像与视频处理 · 电气工程与系统科学 2023-08-29 Aysen Degerli , Fahad Sohrab , Serkan Kiranyaz , Moncef Gabbouj

Nowadays, Breast cancer has risen to become one of the most prominent causes of death in recent years. Among all malignancies, this is the most frequent and the major cause of death for women globally. Manually diagnosing this disease…

机器学习 · 计算机科学 2022-07-01 Taminul Islam , Arindom Kundu , Nazmul Islam Khan , Choyon Chandra Bonik , Flora Akter , Md Jihadul Islam

Heart disease is a serious worldwide health issue because it claims the lives of many people who might have been treated if the disease had been identified earlier. The leading cause of death in the world is cardiovascular disease, usually…

机器学习 · 计算机科学 2024-09-10 Akua Sekyiwaa Osei-Nkwantabisa , Redeemer Ntumy

Smoking continues to be a major preventable cause of death worldwide, affecting millions through damage to the heart, metabolism, liver, and kidneys. However, current medical screening methods often miss the early warning signs of…

机器学习 · 计算机科学 2026-01-27 Vaskar Chakma , MD Jaheid Hasan Nerab , Abdur Rouf , Abu Sayed , Hossem MD Saim , Md. Nournabi Khan

Current prognostic risk scores in cardiac surgery are based on statistics and do not yet benefit from machine learning. Statistical predictors are not robust enough to correctly identify patients who would benefit from Transcatheter Aortic…

机器学习 · 计算机科学 2020-01-09 Marco Mamprin , Jo M. Zelis , Pim A. L. Tonino , Svitlana Zinger , Peter H. N. de With

Objective: Machine learning (ML) predictive models are often developed without considering downstream value trade-offs and clinical interpretability. This paper introduces a cost-aware prediction (CAP) framework that combines cost-benefit…

Gradient Boosting Machines (GBM) are hugely popular for solving tabular data problems. However, practitioners are not only interested in point predictions, but also in probabilistic predictions in order to quantify the uncertainty of the…

机器学习 · 计算机科学 2021-06-08 Olivier Sprangers , Sebastian Schelter , Maarten de Rijke

This paper proposes a hybrid framework combining LSTM (Long Short-Term Memory) networks with LightGBM and CatBoost for stock price prediction. The framework processes time-series financial data and evaluates performance using seven models:…

机器学习 · 计算机科学 2025-05-30 Chang Yu , Fang Liu , Jie Zhu , Shaobo Guo , Yifan Gao , Zhongheng Yang , Meiwei Liu , Qianwen Xing

Hypertension and atrial fibrillation (AF) often coexist in critically ill patients, significantly increasing mortality rates in the ICU. Early identification of high-risk individuals is crucial for targeted interventions. However, limited…

应用统计 · 统计学 2025-06-19 Shuheng Chen , Yong Si , Junyi Fan , Li Sun , Greg Placencia , Elham Pishgar , Kamiar Alaei , Maryam Pishgar

The use of credit cards has recently increased, creating an essential need for credit card assessment methods to minimize potential risks. This study investigates the utilization of machine learning (ML) models for credit card default…

机器学习 · 计算机科学 2023-10-17 Anas Arram , Masri Ayob , Musatafa Abbas Abbood Albadr , Alaa Sulaiman , Dheeb Albashish

We research into the clinical, biochemical and neuroimaging factors associated with the outcome of stroke patients to generate a predictive model using machine learning techniques for prediction of mortality and morbidity 3 months after…

Heart disease is the leading cause of death worldwide. Currently, 33% of cases are misdiagnosed, and approximately half of myocardial infarctions occur in people who are not predicted to be at risk. The use of Artificial Intelligence could…

机器学习 · 计算机科学 2020-07-28 Sahithi Ankireddy

Early hospital mortality prediction is critical as intensivists strive to make efficient medical decisions about the severely ill patients staying in intensive care units. As a result, various methods have been developed to address this…

机器学习 · 计算机科学 2019-02-12 Reza Sadeghi , Tanvi Banerjee , William Romine

Coronary heart disease, which is a form of cardiovascular disease (CVD), is the leading cause of death worldwide. The odds of survival are good if it is found or diagnosed early. The current report discusses a comparative approach to the…

计算机视觉与模式识别 · 计算机科学 2021-12-03 Kelvin Kwakye , Emmanuel Dadzie

Cardiovascular disease (CVD) remains a critical global health concern, demanding reliable and interpretable predictive models for early risk assessment. This study presents a large-scale analysis using the Heart Disease Health Indicators…

机器学习 · 计算机科学 2025-11-05 Md Abrar Hasnat , Md Jobayer , Md. Mehedi Hasan Shawon , Md. Golam Rabiul Alam