AIMC Topic: Heart Diseases

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Nanocomposites of gold nanoparticles and graphene oxide towards an stable label-free electrochemical immunosensor for detection of cardiac marker troponin-I.

Analytica chimica acta
A stable label-free amperometric immunosensor is presented based on gold nanoparticles and graphene oxide nanocomposites for detection of cardiac troponin-I in the early diagnosis of myocardial infarction. For designing of the sensing platform, first...

SIM-ELM: Connecting the ELM model with similarity-function learning.

Neural networks : the official journal of the International Neural Network Society
This paper moves from the affinities between two well-known learning schemes that apply randomization in the training process, namely, Extreme Learning Machines (ELMs) and the learning framework using similarity functions. These paradigms share a com...

Prediction of hospitalization due to heart diseases by supervised learning methods.

International journal of medical informatics
BACKGROUND: In 2008, the United States spent $2.2 trillion for healthcare, which was 15.5% of its GDP. 31% of this expenditure is attributed to hospital care. Evidently, even modest reductions in hospital care costs matter. A 2009 study showed that n...

Artificial Intelligence Analysis of Chest Radiographs for Predicting Major Adverse Events in Patients Visiting the Emergency Department With Acute Cardiopulmonary Symptoms.

Korean journal of radiology
OBJECTIVE: In this study, we investigated whether artificial intelligence (AI) analysis of chest radiographs (CXRs) can predict major adverse clinical events in patients visiting the emergency department (ED) with acute cardiopulmonary symptoms.

Machine learning algorithms for heart disease diagnosis: A systematic review.

Current problems in cardiology
BACKGROUND: The heart is a vital organ that pumps blood throughout the body. Its proper functioning is crucial for maintaining overall health, and any malfunction can significantly impact other bodily systems. Recently, machine learning has emerged a...

Highlights 2024.

Radiology. Cardiothoracic imaging
publishes research, technical developments, and reviews related to cardiac, vascular, and thoracic imaging. The current review article, led by the trainee editorial board, highlights the most impactful articles published in the journal between Nove...

Eigenhearts: Cardiac diseases classification using eigenfaces approach.

Computers in biology and medicine
In the realm of cardiovascular medicine, medical imaging plays a crucial role in accurately classifying cardiac diseases and making precise diagnoses. However, the integration of data science techniques in this field presents significant challenges, ...

Optimizing stability of heart disease prediction across imbalanced learning with interpretable Grow Network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Heart disease prediction models often face stability challenges when applied to public datasets due to significant class imbalances, unlike the more balanced benchmark datasets. These imbalances can adversely affect various...

IoT driven smart health monitoring for heart disease prediction using quantum kernel enhanced sardine diffusion and CNN.

Scientific reports
Heart disease is one of the major causes of death worldwide, and the traditional diagnostic procedures typically cause delays in treatment, particularly in low-resource regions. In this article, we propose a novel IoT-based Quantum Kernel-Enhanced Sa...

Telecardiology unleashed: probing the depths of effectiveness in remote monitoring and telemedicine applications for acute cardiac conditions.

European heart journal. Acute cardiovascular care
Telecardiology has emerged as a promising approach in acute cardiac care through advancements in digital health technologies. This review explores the current evidence of telemedicine applications in acute coronary syndrome, arrhythmias, and acute he...