MSc Thesis Defense - Computer Science: Tanner Boyle

Please join the Department of Computer Science for the upcoming thesis defense:

Presenter: Tanner Boyle

Thesis title: A Leakage-Aware and Reliability-Focused Evaluation Framework for Multiclass Alzheimer’s Disease Staging Using MRI Slices

Abstract: Two-dimensional magnetic resonance imaging (MRI) studies of Alzheimer’s disease (AD) can overestimate performance when slices from the same subject appear in both training and assessment sets. This thesis evaluated a leakage-aware framework for multiclass AD staging based on subject-independent partitioning, subject-level prediction, calibration, and external validation.

Three model families were compared on 347 OASIS subjects using subject-wise crossvalidation: a convolutional neural network (CNN), a Vision Transformer (ViT), and a Hybrid CNN–ViT architecture. A matched slice-random ablation quantified leakageassociated inflation. Supporting analyses examined imbalance-aware objectives and subject-level reliability. Generalizability was tested on 502 ADNI subjects after OASIS model-selection decisions were fixed.

Slice-random evaluation contaminated 98.3% of assessment subjects and inflated macro- F1 by 0.252–0.288. Under subject-wise evaluation, the Hybrid achieved the highest OASIS macro-F1 (0.711). On ADNI, the ViT achieved the highest external macro-F1 (0.718), reversing the internal ranking. These findings show that evaluation protocol and independent cohort testing can materially change conclusions about model quality.


Committee Members:
Dr. Garima Bajwa (supervisor, committee chair), Dr. Abedalrhman Alkhateeb, Dr. Thangarajah Akilan (Software Engineering), Dr. Dominique Cava (Thunder Bay Regional Health Research Institute)


Please contact grad.compsci@lakeheadu.ca for the Zoom link. Everyone is welcome.