1. REU WEEK 8 Nancy Zanaty, UCF

2. Past approach modified  Previously: Classifying individual images in a timeseries as “ADHD” or “Non ADHD” as a test of the SVM  Able to obtain around 65-75% for individual images

3. New approach: Majority  Classify as “ADHD” or “Non ADHD” based on what the majority of the time series is classified as

5. SVM Results  From past data, 2/3 brains were classified correctly. The brains that were classified incorrectly by only a small margin. Meaning that around 45% of the timeseries was correct but not enough to be majority

7. Problems  Tried to expand data to classify more brains, but was too large for SVM  Had to cut down data but sample wasn’t wasn’t broad enough to be accurate  Only about 50-60% were classified accurately

8. Next steps  Resizing images or looking to different data sets  Train SVM on larger samples and begin classifying more brains