A Review on Heart Disease Detection Techniques

2017 ◽  
Vol 7 (7) ◽  
pp. 395
Author(s):  
. Anika ◽  
Navpreet Kaur
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Review Paper ◽  
Vascular Diseases ◽  
Disease Detection ◽  
Automated Classification ◽  
Feature Extraction Method ◽  
Detection Techniques ◽  
Cardio Vascular ◽  
Public Domain Software

The paper exhibits a formal audit on early detection of heart disease which are the major cause of death. Computational science has potential to detect disease in prior stages automatically. With this review paper we describe machine learning for disease detection. Machine learning is a method of data analysis that automates analytical model building.Various techniques develop to predict cardiac disease based on cases through MRI was developed. Automated classification using machine learning. Feature extraction method using Cell Profiler and GLCM. Cell Profiler a public domain software, freely available is flourished by the Broad Institute's Imaging Platform and Glcm is a statistical method of examining texture .Various techniques to detect cardio vascular diseases.

Heart Disease Detection using Machine Learning Technique

2021 ◽  
Author(s):  
Likitha KN ◽  
Nethravathi R ◽  
Nithyashree K ◽  
Ritika Kumari ◽  
Sridhar N ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Disease Detection ◽  
Machine Learning Technique ◽  
Learning Technique

scholarly journals Review Paper on Prediction of Heart Disease using Machine Learning Algorithms

2021 ◽  
Vol 9 (VI) ◽  
pp. 2937-2940
Author(s):  
Aadar Pandita
Keyword(s):  
Machine Learning ◽  
Heart Disease ◽  
Review Paper ◽  
Heart Diseases ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
The World ◽  
Medical Researchers ◽  
High Level ◽  
The Impact

: Heart disease has been one of the ruling causes for death for quite some time now. About 31% of all deaths every year in the world take place as a result of cardiovascular diseases [1]. A majority of the patients remain uninformed of their symptoms until quite late while others find it difficult to minimise the effects of risk factors that cause heart diseases. Machine Learning Algorithms have been quite efficacious in producing results with a high level of correctness thereby preventing the onset of heart diseases in many patients and reducing the impact in the ones that are already affected by such diseases. It has helped medical researchers and doctors all over the world in recognising patterns in the patients resulting in early detections of heart diseases.

scholarly journals Classification Techniques for Cardio- Vascular Diseases Using Supervised Machine Learning

2020 ◽  
Vol 74 (1) ◽  
pp. 39
Author(s):  
John Minou ◽  
John Mantas ◽  
Flora Malamateniou ◽  
Daphne Kaitelidou
Keyword(s):  
Machine Learning ◽  
Vascular Diseases ◽  
Supervised Machine Learning ◽  
Classification Techniques ◽  
Cardio Vascular

scholarly journals Nitric oxide role in pathogenesis and treatment of cardio-vascular diseases (literature review)

2021 ◽  
Vol 25 (2(98)) ◽  
pp. 130-134
Author(s):  
S. Biletskyi
Keyword(s):  
Nitric Oxide ◽  
Heart Disease ◽  
Essential Hypertension ◽  
Cardiovascular Diseases ◽  
Vascular Diseases ◽  
No Donors ◽  
Comprehensive Therapy ◽  
Nitric Oxide Deficiency ◽  
Cardio Vascular

Literature data concerning the role of endothelium and nitric oxide in the pathogenesis of cardiovascular diseases, administration of L-arginine as a part of a comprehensive therapy of patients suffering from essential hypertension (EH) and ischemic heart disease (IHD) are cited.Objective: to systematize current literature data concerning the role of endothelium and nitric oxide in the pathogenesis of cardiovascular diseases, clinical experience of L-arginine administration in patients with EH and IHD. Conclusion. Nowadays endothelial dysfunction conception is defined with insufficient production of nitric oxide as a central part of EH and IHD pathogenesis. Nitric oxide deficiency occurring with cardiovascular diseases can be compensated by means of NO donors.

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