| Author(s): |
Passos, Leandro A.
;
Pereira, Clayton R.
;
Rezende, Edmar R. S.
;
Carvalho, Tiago J.
;
Weber, Silke A. T.
;
Hook, Christian
;
Papa, Joao P.
;
IEEE
Total Authors: 8
|
| Document type: | Journal article |
| Source: | 2018 IEEE 12TH INTERNATIONAL SYMPOSIUM ON APPLIED COMPUTATIONAL INTELLIGENCE AND INFORMATICS (SACI); v. N/A, p. 5-pg., 2018-01-01. |
| Abstract | |
Known as one of the most significant neurodegenerative diseases of the central nervous system, Parkinson's disease (PD) has a combination of several symptoms, such as tremor, postural instability, loss of movements, depression, anxiety, and dementia, among others. For the medicine, to point an exam that can diagnose a patient with such illness is challenging due to the symptoms that are easily related to other diseases. Therefore, developing computational methods capable of identifying PD in its early stages has been of paramount importance in the scientific community. Thence, this paper proposes to use a deep neural network called ResNet-50 to learn the patterns and extract features from images draw by patients. Afterwards, the Optimum-Path Forest (OPF) classifier is employed to identify Parkinson's disease automatically, being the results compared against two well-known classifiers, i.e., Support Vector Machines and the Bayes, as well as the ones provided by ResNet-50 itself. The experiments showed promising results concerning OPF, reaching over 96% of identification rate. (AU) | |
| FAPESP's process: | 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry |
| Grantee: | Francisco Louzada Neto |
| Support Opportunities: | Research Grants - Research, Innovation and Dissemination Centers - RIDC |
| FAPESP's process: | 16/21243-7 - Learning Dropout Parameters for Convolutional Neural Networks |
| Grantee: | Gustavo Henrique de Rosa |
| Support Opportunities: | Scholarships abroad - Research Internship - Master's degree |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 15/25739-4 - On the Study of Semantics in Deep Learning Models |
| Grantee: | Gustavo Henrique de Rosa |
| Support Opportunities: | Scholarships in Brazil - Master |
| FAPESP's process: | 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms |
| Grantee: | João Paulo Papa |
| Support Opportunities: | Regular Research Grants |