Name
Title | ||
|---|---|---|
An LDA and probability-based classifier for the diagnosis of Alzheimer's Disease from structural MRI |
Abstract | ||
|---|---|---|
In this paper a custom classification algorithm based on linear discriminant analysis and probability-based weights is implemented and applied to the hippocampus measurements of structural magnetic resonance images from healthy subjects and Alzheimer's Disease sufferers; and then attempts to diagnose them as accurately as possible. The classifier works by classifying each measurement of a hippocampal volume as healthy control-sized or Alzheimer's Disease-sized, these new features are then weighted and used to classify the subject as a healthy control or suffering from Alzheimer's Disease. The preliminary results obtained reach an accuracy of 85.8% and this is a similar accuracy to state-of-the-art methods such as a Naive Bayes classifier and a Support Vector Machine. An advantage of the method proposed in this paper over the aforementioned state-of-the-art classifierst is the descriptive ability of the classifications it produces. The descriptive model can be of great help to aid a doctor in the diagnosis of Alzheimer's Disease, or even further the understand of how Alzheimer's Disease affects the hippocampus. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/BIBM.2015.7359883 | IEEE International Conference on Bioinformatics and Biomedicine |
Field | DocType | ISSN |
Disease,Healthy control,Pattern recognition,Naive Bayes classifier,Computer science,Support vector machine,Artificial intelligence,Linear discriminant analysis,Classifier (linguistics),Machine learning | Conference | 2156-1125 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Alexander Luke Spedding | 1 | 1 | 0.69 |
| Giuseppe Di Fatta | 2 | 529 | 39.23 |
| James Douglas Saddy | 3 | 0 | 0.34 |