Obstructive coronary artery disease diagnostics: machine learning approach for an effective preselection of patients

2022 ◽  
pp. 219-244
Author(s):  
Mateusz Krysiński ◽  
Małgorzata Krysińska ◽  
Ewaryst Tkacz
Keyword(s):  
Machine Learning ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Obstructive Coronary Artery Disease ◽  
Learning Approach ◽  
Disease Diagnostics ◽  
Machine Learning Approach ◽  
Artery Disease

scholarly journals A Novel Technique for Prediction of Coronary Artery Disease from Human Fundus Images Using Machine Learning Approach

2020 ◽  
pp. 655-661
Keyword(s):  
Machine Learning ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Learning Approach ◽  
Fundus Image ◽  
Novel Technique ◽  
Machine Learning Approach ◽  
Flow Through ◽  
Artery Disease ◽  
Cad Risk

Traditionally, Coronary Artery Disease (CAD) is detected only when the person got a heart stroke. The coronary arteries blockages are identified by using a technique called Angiogram test, where a thin wire called catheter is inserted into an artery present in groin or arm and passed through the vessel to reach to heart. Later after identification of coronary artery blockages Angioplasty procedure is done to restore blood flow through the artery. The organ through which blood vessels are clearly visible is Eye. So, our research is in the line of detecting Coronary Artery Disease (CAD) by analysing fundus image of human eye instead of traditional process which is costlier and painful process. Through this technique we can help patients by knowing about the risk of CAD early before having symptoms of heart attack. Machine Learning and Image Processing [10,11] approaches are used in this work of early detection of CAD risk. This is an innovative attempt of detecting Coronary Artery Disease.

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