s4693608 - Alzheimer's Classifier (Task 8)#293
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CHAR1VAR1 wants to merge 31 commits intoshakes76:topic-recognitionfrom
Open
s4693608 - Alzheimer's Classifier (Task 8)#293CHAR1VAR1 wants to merge 31 commits intoshakes76:topic-recognitionfrom
CHAR1VAR1 wants to merge 31 commits intoshakes76:topic-recognitionfrom
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…t normalisation to use true mean/std values
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This is an initial inspection, no action is required at this pointRecognition Problem : total : 10.5
Note:
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Marking
Marked as per the due date and changes after which aren't necessarily allowed to contribute to grade for fairness. |
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This project implements a deep learning classifier to distinguish between Alzheimer’s Disease (AD) and Normal Control (NC) using 2D MRI brain slices from the ADNI dataset. The model is based on ConvNeXt, trained using PyTorch, and makes predictions on the slice-level and then aggregates through these predictions and averages them to make patient-level predictions. The model was trained and tested on UQ’s rangpur, achieving a final patient prediction accuracy of 80.22.