New Improved Genetic Algorithm for Coronary Heart Disease Prediction
Author(s) -
Waheeda Dhokley,
Tahreem Ansari,
Naeema Fazlani,
H. M. Abdel Hafeez
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016908419
Subject(s) - computer science , genetic algorithm , algorithm , artificial intelligence , machine learning
Heart disease prediction is treated as most complicated task in the field of medical sciences. Thus there arises a need to build a decision support system for detecting heart disease of a patient. Almost all system predicting heart disease use inputs from complex tests conducted in labs. In this project we are developing a system which will predict heart based on the risk factors such as tobacco, smoking, alcohol intake, age, family history, diabetes, hypertension, high cholesterol, physical inactivity, obesity. These common risk factors can be used effectively for diagnosis of heart disease[1]. System based on the such risk factors would not only help medical professionals but it would give patients a warning about the probable presence of the heart disease even before he/she visits a hospital or goes for costly medical checkups. General Terms Artificial Intelligence, heart disease, risk factor
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom