Research on Appointment Scheduling of CT Examination Based on Genetic Algorithm

2021 ◽  
Author(s):  
Xinyu Bai ◽  
Junqing Sun
Keyword(s):  
Genetic Algorithm ◽  
Appointment Scheduling ◽  
Ct Examination

A hybrid genetic algorithm for appointment scheduling in a health examination system

2020 ◽  
Vol 11 (4) ◽  
pp. 293
Author(s):  
Atabak Iranizad ◽  
Ali Ala ◽  
Sajjad Ebadi Torkayesh ◽  
Ali Ebadi Torkayesh
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Appointment Scheduling ◽  
Health Examination ◽  
Examination System

A hybrid genetic algorithm for appointment scheduling in a health examination system

2020 ◽  
Vol 11 (4) ◽  
pp. 293
Author(s):  
Ali Ala ◽  
Sajjad Ebadi Torkayesh ◽  
Ali Ebadi Torkayesh ◽  
Atabak Iranizad
Keyword(s):  
Genetic Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Appointment Scheduling ◽  
Health Examination ◽  
Examination System

The ground state energy of the ±J spin glass from the genetic algorithm

1994 ◽  
Vol 4 (9) ◽  
pp. 1281-1285 ◽  
Author(s):  
P. Sutton ◽  
D. L. Hunter ◽  
N. Jan
Keyword(s):  
Genetic Algorithm ◽  
Spin Glass ◽  
Ground State Energy ◽  
Ground State ◽  
State Energy

A Comparative Study of Ant and Genetic Algorithms in Digital Mammography

2018 ◽  
pp. 194-200
Author(s):  
J. Magelin Mary ◽  
Chitra K. ◽  
Y. Arockia Suganthi
Keyword(s):  
Genetic Algorithm ◽  
Image Processing ◽  
Medical Image ◽  
Medical Image Processing ◽  
Processing Technique ◽  
Input Image ◽  
Image Processing Technique ◽  
Computational Time ◽  
Image Mining ◽  
The Individual

Image processing technique in general, involves the application of signal processing on the input image for isolating the individual color plane of an image. It plays an important role in the image analysis and computer version. This paper compares the efficiency of two approaches in the area of finding breast cancer in medical image processing. The fundamental target is to apply an image mining in the area of medical image handling utilizing grouping guideline created by genetic algorithm. The parameter using extracted border, the border pixels are considered as population strings to genetic algorithm and Ant Colony Optimization, to find out the optimum value from the border pixels. We likewise look at cost of ACO and GA also, endeavors to discover which one gives the better solution to identify an affected area in medical image based on computational time.

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