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A Deep Transfer Learning Model for the Analysis of Electrocardiograms
Published in Hassan Ugail, Deep Learning in Visual Computing, 2022
Coronary heart diseases are one of the primary causes of human deaths in the world. Over 17.7 million people die every year due to cardiovascular-related diseases. Heart attacks amount to over 70% of such deaths [1]. The leading cause of heart attacks is the inadequate ability for blood to flow within the heart’s coronary arteries, causing a medical condition known as myocardial infarction (MI).
Comparative Assessment of Machine-Learning Based Methodologies and Algorithms with Accuracy, Sensitivity and Specificity for Prediction of Heart Disease
Published in Durgesh Kumar Mishra, Nilanjan Dey, Bharat Singh Deora, Amit Joshi, ICT for Competitive Strategies, 2020
Rahul Kumar Jha, Santosh Kumar Henge
Myocardial infarction (MI), known as heart attack occurs due to abrupt behaviour of blood flow to a part of heart causing damage to the heart muscle, is a medical emergency requiring immediate attention and cure (Myocardial infarction n.d.). Owing to blockage of coronary artery fully or partially due to accretion of cholesterol plaque in the inner artery, blood flow rate diminishes to the heart tissue, causing tissues around the artery to die because of insufficient oxygen supply thereby afilters heart conduction (4 Steps of Cardiac Conduction n.d.), causing to cardiac blockage which may leads to immense circumstances even to sudden death. Symptoms includes disquieting pain in chest, arms, left shoulder, elbows, jaw or back; sweating; breathing problem; dizziness; high blood pressure; nausea and fatigue which causes due to chain smoking, excessive alcohol intake, lack of exercise, high level of cholesterol, diabetes, obesity, unhealthy diet and can be prevented addressing these (Strategies to prevent heart disease n.d.). Early diagnosis of heart disease is very important to cure the disease and many parameters can be used to detect the disease at early stage i.e. heart rate HR), pulse rate, sugar level, cholesterol, blood pressure (BP), body temperature (BT), oxygen level (SpO2), electrocardiogram (ECG) signals and echocardiography.
Intravenous Immunoglobulin at the Borderline of Nanomedicines and Biologicals: Antithrombogenic Effect via Complement Attenuation
Published in Raj Bawa, János Szebeni, Thomas J. Webster, Gerald F. Audette, Immune Aspects of Biopharmaceuticals and Nanomedicines, 2019
Atherosclerosis is the major risk factor associated with the onset of cardiovascular disorders such as stroke and myocardial infarction. It is recognized as a typical chronic inflammatory condition in which inflammation, triggered by complement activation, plays a fundamental role in the development and progression of atherosclerotic lesion formation, plaque rupture, and thrombosis [3].
Recent advances in micro-sized oxygen carriers inspired by red blood cells
Published in Science and Technology of Advanced Materials, 2023
Qiming Zhang, Natsuko F. Inagaki, Taichi Ito
Myocardial infarction is caused by the occlusion of a coronary artery, leading to the depletion of oxygen from cardiac tissue. Thus, myocardial cells in the infarcted areas under hypoxia lose their functions and undergo cell death. A sufficient and continuous oxygen supply is necessary to overcome the hypoxic conditions of damaged cardiac tissues. In 2005, Radisic et al. reported that PFC emulsions were effective in myocardial protection therapy, based on a mathematical model of oxygen distribution from the PFC and experiments on rat neonatal cardiac tissues cultured in a medium supplemented with PFC emulsions [135]. Liu et al. showed that a single dose of a dodecafluoropentane -based perfluorocarbon emulsion could significantly reduce myocardial injury in a rat myocardial ischemia model using 99mTc-duramycin single-photon emission computed tomography imaging [150]. Furthermore, Qin et al. showed that pigment epithelium-derived factor-loaded PFC nanoemulsions reduced ischemic myocardial injuries in a rat myocardial ischemia model [151].
A profile on the CardioMEMS HF system in the management of patients with early stages of heart failure: an update
Published in Expert Review of Medical Devices, 2023
Rohit Vyas, Mitra Patel, Samer J. Khouri, George V. Moukarbel
The safety and accuracy of the CardioMEMS HF system has been studied extensively and was demonstrated in multiple studies: the CHAMPION trial, the US CardioMEMS Post-approval study, GUIDE HF, and post-marketing surveillance data in ‘Manufacturer and User Facility Device Experience’ (MAUDE) [12,15,32,43]. Generally, potential complications include arrhythmias, bleeding, death, device embolization, hematoma, infection, myocardial infarction, stroke/transient ischemic attack, and thrombus formation. At 6-month follow-up in the CHAMPION trial, there were a total of 15 adverse events (2.6%). Of those, eight were DSRC (1%) and seven were procedure-related complications (1%). This included a single case of PA injury and two deaths. No additional DSRC or sensor failure events were observed at 31 months in the extended follow-up study. Patients had 98.6% freedom from DSRC and no pressure-sensor failures occurred in the 550 patients enrolled in the study [12]. The safety of CardioMEMS appears to be comparable to that of right heart catheterization (RHC) [44,45].
Identification of coronary artery stenosis based on hybrid segmentation and feature fusion
Published in Automatika, 2023
K. Kavipriya, Manjunatha Hiremath
Coronary artery disease (CAD), is the most common type of cardiovascular diseases and a major cause of mortality worldwide in the last decade. When the coronary arteries are narrowed or blocked induced by the atheromatous plaques building up inside, the reduction of oxygen-rich blood flow to the heart muscle can cause angina or a myocardial infarction. The fundamental task required for the interpretation of coronary angiography is identification and quantification of severity of stenosis within the coronary circulation. However, with the complex vessel structure, image noise, poor contrast and non-uniform illumination appearing in the angiograms, the maximum degree of coronary artery stenosis cannot be always accurately evaluated.