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Lauren M. Paladino, Alexander Hughes, Alexander Perera, Oguzhan Topsakal and Tahir Cetin Akinci
Globally, over 17 million people annually die from cardiovascular diseases, with heart disease being the leading cause of mortality in the United States. The ever-increasing volume of data related to heart disease opens up possibilities for employing mac...
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Daniyal Asif, Mairaj Bibi, Muhammad Shoaib Arif and Aiman Mukheimer
Heart disease is a significant global health issue, contributing to high morbidity and mortality rates. Early and accurate heart disease prediction is crucial for effectively preventing and managing the condition. However, this remains a challenging task...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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Chintan M. Bhatt, Parth Patel, Tarang Ghetia and Pier Luigi Mazzeo
The diagnosis and prognosis of cardiovascular disease are crucial medical tasks to ensure correct classification, which helps cardiologists provide proper treatment to the patient. Machine learning applications in the medical niche have increased as they...
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Muhammad Mateen Yaqoob, Muhammad Nazir, Muhammad Amir Khan, Sajida Qureshi and Amal Al-Rasheed
One of the deadliest diseases, heart disease, claims millions of lives every year worldwide. The biomedical data collected by health service providers (HSPs) contain private information about the patient and are subject to general privacy concerns, and t...
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Jian Yang and Jinhan Guan
In today?s world, heart disease is the leading cause of death globally. Researchers have proposed various methods aimed at improving the accuracy and efficiency of the clinical diagnosis of heart disease. Auxiliary diagnostic systems based on machine lea...
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Heba Aly Elzeheiry, Sherief Barakat and Amira Rezk
In recent years, medical data have vastly increased due to the continuous generation of digital data. The different forms of medical data, such as reports, textual, numerical, monitoring, and laboratory data generate the so-called medical big data. This ...
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Roberto Porto, José M. Molina, Antonio Berlanga and Miguel A. Patricio
Learning systems have been focused on creating models capable of obtaining the best results in error metrics. Recently, the focus has shifted to improvement in the interpretation and explanation of the results. The need for interpretation is greater when...
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Md Nasim Adnan,Md Zahidul Islam
Decision trees are popularly used in a wide range of real world problems for both prediction and classification (logic) rules discovery. A decision forest is an ensemble of decision trees and it is often built for achieving better predictive performance ...
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Shadi AlZu?bi, Mohammad Elbes, Ala Mughaid, Noor Bdair, Laith Abualigah, Agostino Forestiero and Raed Abu Zitar
Diabetes is a metabolic disorder in which the body is unable to properly regulate blood sugar levels. It can occur when the body does not produce enough insulin or when cells become resistant to insulin?s effects. There are two main types of diabetes, Ty...
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Nellyzeth Flores, Marco A. Reyna, Roberto L. Avitia, Jose Antonio Cardenas-Haro and Conrado Garcia-Gonzalez
Cardiovascular disease (CVD) is a global public health problem. It is a disease of multifactorial origin, and with this characteristic, having an accurate diagnosis of its incidence is a problem that health personnel face every day. That is why having al...
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Amna Al-Sayed, Mashael M. Khayyat and Nuha Zamzami
Different data types are frequently included in clinical data. Applying machine learning algorithms to mixed data can be difficult and impact the output accuracy and quality. This paper proposes a hybrid model of unsupervised and supervised learning tech...
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Fu-I Chou, Tian-Hsiang Huang, Po-Yuan Yang, Chin-Hsuan Lin, Tzu-Chao Lin, Wen-Hsien Ho and Jyh-Horng Chou
This study proposes a method to improve fractional-order particle swarm optimizer to overcome the shortcomings of traditional swarm algorithms, such as low search accuracy in a high-dimensional space, falling into local minimums, and nonrobust results. I...
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Narendra Kurnia Putra, Bonfilio Nainggolan, Johanna Muliany, S Suprijanto
Pág. 54 - 60
Cardiovascular diseases are the world?s leading cause of death with significant death rates caused by abnormalities in vessels such as aneurysms and stenosis. These conditions can potentially cause blockage and thinning of vessels which may lead to heart...
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Narendra Kurnia Putra, Bonfilio Nainggolan, Johanna Muliany, S Suprijanto
Pág. 54 - 60
Cardiovascular diseases are the world?s leading cause of death with significant death rates caused by abnormalities in vessels such as aneurysms and stenosis. These conditions can potentially cause blockage and thinning of vessels which may lead to heart...
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Subramanyam Shashi Kumar and Prakash Ramachandran
Nowadays, healthcare is becoming very modern, and the support of Internet of Things (IoT) is inevitable in a personal healthcare system. A typical personal healthcare system acquires vital parameters from human users and stores them in a cloud platform f...
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