Comparison of our classical–quantum and pure classical models with recent literature approaches for AD detection, highlighting key attributes such as dataset, number of classes, model type, GPU support , segmentation usage , accuracy, parameter count, and model size.

<p>Comparison of our classical–quantum and pure classical models with recent literature approaches for AD detection, highlighting key attributes such as dataset, number of classes, model type, GPU support , segmentation usage , accuracy, parameter count, and model size.</p>

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Bibliografske podrobnosti
Glavni avtor:	Mominul Islam (3513758) (author)
Drugi avtorji:	Mohammad Junayed Hasan (21464229) (author), M.R.C. Mahdy (22290983) (author)
Izdano:	2025
Teme:	Medicine Cell Biology Biotechnology Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified simple preprocessing framework face difficulties converging 2 dataset reveal 05 mb ), develop automated systems based automated systems far fewer parameters alzheimer &# 8217 promising quantum advantage parameterized quantum circuit div >< p replace classical systems quantum model demonstrates >( iii )</ >( ii )</ current hybrid classical quantum systems hybrid classical classical model alzheimer ’ 7k parameters quantum models quantum computing quantum computers quantum architectures generation classical classical models significant limitation results highlight practical deployment parameter count optimization stagnation moderate dementia highly similar gradient failure emerging demands domain expertise domain challenge dementia classes cnns ). class images automatic detection attaining state art accuracy accuracy using 2d slices
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Comparison of our classical–quantum and pure classical models with recent literature approaches for AD detection, highlighting key attributes such as dataset, number of classes, model type, GPU support , segmentation usage , accuracy, parameter count, and model size.

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