- author = "Mohamad Roshanzamir and Mohammad Tayarani Darbandy and Mahdi Roshanzamir and Roohallah Alizadehsani and Afshin Shoeibi",
- title = "Genetic Programming for optimization of {CAD} detection process",
- booktitle = "2021 IEEE 4th International Conference and Workshop Obuda on Electrical and Power Engineering (CANDO-EPE)",
- year = "2021",
- pages = "65--70",
- month = "17-18 " # nov,
- address = "Budapest, Hungary",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-1-6654-2024-2",
-
DOI = "
doi:10.1109/CANDO-EPE54223.2021.9667921",
- abstract = "Genetic Programming (GP) is one type of evolutionary algorithm used in optimizing decision-making and control processes in one/multi agent systems. In this research, this algorithm is used to optimize the Coronary Artery Disease (CAD) diagnosis process. CAD is a heart disease that unfortunately has a high mortality rate among humans. Different methods have been developed for CAD detection, each with different accuracy. In addition, the diagnosis process will have different expenses and times for medical examination depending on the chosen method. In this study, using GP algorithm, we try to optimize the expense and time of diagnosis of this disease when different diagnostic methods are used. Optimizing time and expense is important for all physicians during their careers. Even time management is important for physicians and patients. These management and optimization help them to increase their productivity, decrease stress, improve their satisfaction, and decrease their burnouts. Both the patient and the physician can select the diagnostic method according to the available expense and time. They are also able to have the accuracy rate of the selected method. During the evolution process of GP, it considers which type of features such as Demographic, Symptom and examination, Laboratory and echo and ECG can achieve the required accuracy considering requested expense and time.",
-
notes = "Also known as \cite{9667921}
Faculty of Engineering, Fasa University, 74617-81189, Fasa, Iran",
