Assessment of Alzheimer image detection on CNN ensemble model fine-tuned with genetic algorithm

Herrera Padilla, Carlos Angel (2024) Assessment of Alzheimer image detection on CNN ensemble model fine-tuned with genetic algorithm. Masters thesis, Dublin, National College of Ireland.

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Abstract

Alzheimer’s is a brain disease that affects millions of people around the world, by 2060 it is estimated that more than 14 million people in the United States will be diagnosed with this disease. The importance of detecting Alzheimer’s in an individual could change their life, even though Alzheimer’s is a disease with no cure, the detection of Alzheimer’s could delay or slow the symptoms, one of the many tasks that machine learning is exceeding is in classification problems. Convolutional Neural Network (CNN) models are commonly used to classify images in the health industry. For this reason, a simple custom CNN model is developed so that it goes through fine-tuning with a genetic algorithm, making an ensemble model of the three best models of the genetic algorithm. This project assesses the performance of the proposed model against state-of-the-art pre-trained ensemble models. The proposed model had an Area Under the Receiver Operating Characteristic Curve (ROC AUC) score of 0.773 and has the third-best performance against ensemble models of pre-trained models like the VGG16, Inceptionv3, and the ResNet50.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Haque, Rejwanul UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RB Pathology R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry Q Science > QH Natural history > QH301 Biology > Methods of research. Technique. Experimental biology > Data processing. Bioinformatics > Artificial intelligence Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Artificial intelligence
Divisions:	School of Computing > Master of Science in Artificial Intelligence
Depositing User:	Tamara Malone
Date Deposited:	03 Apr 2025 18:30
Last Modified:	03 Apr 2025 18:30
URI:	https://norma.ncirl.ie/id/eprint/7366

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