Abstract
Artificial neural networks are being used in diagnosis support systems to detect different kind of diseases. As the design of multilayer perceptron is an open question, the present work shows a comparison between a traditional empirical way and neuroevolution method to find the best architecture to solve the disease detection problem. Tuberculosis and appendicitis databases were employed to test both proposals. Results show that neuroevolution offers a good alternative for the tuberculosis problem but there is lacks of performance in the appendicitis one.
| Original language | English (US) |
|---|---|
| Title of host publication | Applied Computer Sciences in Engineering - 5th Workshop on Engineering Applications, WEA 2018, Proceedings |
| Editors | Eduyn Ramiro Lopez-Santana, Juan Carlos Figueroa-Garcia, Jose Ignacio Rodriguez-Molano |
| Publisher | Springer |
| Pages | 171-181 |
| Number of pages | 11 |
| ISBN (Print) | 9783030003494 |
| DOIs | |
| State | Published - 2018 |
| Externally published | Yes |
| Event | 5th Workshop on Engineering Applications, WEA 2018 - Medellín, Colombia Duration: Oct 17 2018 → Oct 19 2018 |
Publication series
| Name | Communications in Computer and Information Science |
|---|---|
| Volume | 915 |
| ISSN (Print) | 1865-0929 |
Conference
| Conference | 5th Workshop on Engineering Applications, WEA 2018 |
|---|---|
| Country/Territory | Colombia |
| City | Medellín |
| Period | 10/17/18 → 10/19/18 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Mathematics
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