Name
Abstract | ||
|---|---|---|
Various gadgets and medical devices collect data from patients continuously. Processing this information and learning from it is a challenge for data scientists as this kind of data comes in complex and large quantities, making the decision of what kind of algorithms to apply for the best results difficult and time consuming. In this paper we propose a Multi-agent system that enables autonomous selection and application of machine learning methods for data sets belonging to medical systems, by applying genetic algorithms to agents. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/SYNASC.2017.00064 | 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) |
Keywords | Field | DocType |
Evolutionary Multi-agent System,Ambient Intelligence,Smart Hospital,Genetic Algorithms,Machine Learning | Data set,Computer science,Medical systems,Evolutionary computation,Theoretical computer science,Artificial intelligence,Machine learning,Genetic algorithm | Conference |
ISSN | ISBN | Citations |
2470-8801 | 978-1-5386-2627-6 | 1 |
PageRank | References | Authors |
0.40 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Adriana Dinis | 1 | 1 | 1.41 |
| Todor Ivascu | 2 | 1 | 0.73 |
| Viorel Negru | 3 | 311 | 47.71 |