dc.contributor.author |
Eaton, Pipuni Lakshara |
|
dc.date.accessioned |
2021-07-04T15:10:30Z |
|
dc.date.available |
2021-07-04T15:10:30Z |
|
dc.date.issued |
2020 |
|
dc.identifier.citation |
Eaton, Pipuni Lakshara (2020)Angi detect: Fuzzy Rule-Based Approach For Angina Prediction using Symptoms,BSc. Dissertation Informatics Institute of Technology |
en_US |
dc.identifier.other |
2015172 |
|
dc.identifier.uri |
http://dlib.iit.ac.lk/xmlui/handle/123456789/542 |
|
dc.description.abstract |
Cardiovascular Diseases are the number One cause of death globally. Angina is a warning sign of a Heart Attack. Most of the people experience angina before having heart attack. Angina Pectoris does not cause permanent heart damage like heart attacks. If Angina can be detected earlier, doctor can provide the patient proper medication to cure and save life.
ANGI Detect is an expert system which can predict Angina using symptoms and predict the risk level of Angina patient using risk factors. ANGI Detect collected expert knowledge from Cardiovascular experts and research publications, then created the rule base. Considering the fuzziness of Angina symptoms and risk factors, here it used FUZZY LOGICS to implement the core function of ANGI Detect. |
en_US |
dc.subject |
Angina |
en_US |
dc.subject |
expert systems |
en_US |
dc.subject |
Fuzzy Logics |
en_US |
dc.title |
Angi detect: Fuzzy Rule-Based Approach For Angina Prediction using Symptoms |
en_US |
dc.type |
Thesis |
en_US |