{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/towards-alzheimers-disease-classification","title":"Towards Alzheimer's Disease Classification through Transfer Learning","arxiv_id":"1711.11117","date":"2017-11-29","proceeding":null,"authors":["Marcia Hon","Naimul Khan"],"abstract":"Detection of Alzheimer's Disease (AD) from neuroimaging data such as MRI\nthrough machine learning have been a subject of intense research in recent\nyears. Recent success of deep learning in computer vision have progressed such\nresearch further. However, common limitations with such algorithms are reliance\non a large number of training images, and requirement of careful optimization\nof the architecture of deep networks. In this paper, we attempt solving these\nissues with transfer learning, where state-of-the-art architectures such as VGG\nand Inception are initialized with pre-trained weights from large benchmark\ndatasets consisting of natural images, and the fully-connected layer is\nre-trained with only a small number of MRI images. We employ image entropy to\nselect the most informative slices for training. Through experimentation on the\nOASIS MRI dataset, we show that with training size almost 10 times smaller than\nthe state-of-the-art, we reach comparable or even better performance than\ncurrent deep-learning based methods.","url_abs":"http://arxiv.org/abs/1711.11117v1","url_pdf":"http://arxiv.org/pdf/1711.11117v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"towards-alzheimers-disease-classification","repo_url":"https://github.com/marciahon29/Ryerson_MRP","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}