Deep Neural Network for Alzheimer's disease detection
Student thesis: Master Thesis and HD Thesis
- Raquel Cacho Zurrunero
4. term, Innovative Communication Technologies and Entrepreneurship, Master (Master Programme)
The purpose of this thesis is to develop a system that shows how Deep learning can be used to improve the diagnosis of Alzheimer's disease.
The project will be based on the literature review of the disease and the research of the most recent machine learning techniques in order to perform the analysis of a possible solution.
As a result of this analysis, a conceptual design of the system is proposed. The proposed solution will be based on a Multilayer Perception architecture that allows to predict the probability of having the disease based on the patient's clinical data.
Finally, the solution will be implemented and tested, achieving an accuracy of 82.61%.
The project will be based on the literature review of the disease and the research of the most recent machine learning techniques in order to perform the analysis of a possible solution.
As a result of this analysis, a conceptual design of the system is proposed. The proposed solution will be based on a Multilayer Perception architecture that allows to predict the probability of having the disease based on the patient's clinical data.
Finally, the solution will be implemented and tested, achieving an accuracy of 82.61%.
| Language | English |
|---|---|
| Publication date | 2019 |