Name
Title | ||
|---|---|---|
Implementation of biologically motivated optimisation approach for tumour categorisation. |
Abstract | ||
|---|---|---|
Tumour prediction and classification is regarded as a complex task that needs attention. Moreover, medical experts lack expertise in this section. Hence, an intelligent clinical system model is the time of the hour. Recently, biologically motivated techniques are emerging to be an efficient computing method to solve imprecise and complex problems. Nature forms an immense source of motivation in finding solutions to sophisticated problems IT sector since it is highly robust and dynamic. The result obtained is highly optimised and balanced solution. This is the basic idea of such nature motivated techniques. In our research, we have analysed and implemented some important bio-inspired optimisation techniques to categorise different kinds of tumour. Multilayer perceptron is the classifier used in the process. We have later evaluated our results with some critical metrics like RMSE, Kappa coefficient, accuracy and many others to determine the effectiveness of our system model developed. It is observed that us... |
Year | Venue | Field |
|---|---|---|
2018 | IJCAET | Systems engineering,Mean squared error,Cohen's kappa,Multilayer perceptron,Genetic search,Artificial intelligence,Engineering,Classifier (linguistics),System model,Machine learning,Complex problems |
DocType | Volume | Issue |
Journal | 10 | 3 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sushruta Mishra | 1 | 0 | 0.34 |
| Hrudaya K. Tripathy | 2 | 19 | 4.94 |
| Brojo Kishore Mishra | 3 | 6 | 3.55 |