Name
Abstract | ||
|---|---|---|
The heart disease describes a range of conditions affecting our heart. It can include blood vessel diseases such as coronary artery disease, heart rhythm problems or and heart defects. This term is often used for cardiovascular disease, i.e. narrowed or blocked blood vessels leading to a heart attack, chest pain or stroke. In our work, we analysed three available data sets: Heart Disease Database, South African Heart Disease and Z-Alizadeh Sani Dataset. For this purpose, we focused on two directions: a predictive analysis based on Decision Trees, Naive Bayes, Support Vector Machine and Neural Networks; descriptive analysis based on association and decision rules. Our results are plausible, in some cases comparable or better as in other related works. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.15439/2017F219 | 2017 Federated Conference on Computer Science and Information Systems (FedCSIS) |
Keywords | Field | DocType |
heart disease database,decision trees,naive Bayes,support vector machine,neural network,stroke,chest pain,heart attack,blocked blood vessels,cardiovascular disease,heart defects,heart rhythm problems,coronary artery disease,blood vessel diseases,heart disease diagnosis | Decision rule,Coronary artery disease,Decision tree,Data mining,Disease,Computer science,Stroke,Chest pain,Blood vessel,Heart disease | Conference |
ISSN | ISBN | Citations |
2325-0348 | 978-1-5090-4414-6 | 1 |
PageRank | References | Authors |
0.35 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Frantisek Babic | 1 | 16 | 8.02 |
| Jaroslav Olejár | 2 | 1 | 0.69 |
| Zuzana Vantová | 3 | 1 | 0.35 |
| Jan Paralic | 4 | 56 | 13.96 |