Exploring Alzheimer's disease prediction with XAI in various neural network models
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.
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| Формат: | Дисертація |
| Мова: | English |
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Brac University
2022
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| Онлайн доступ: | http://hdl.handle.net/10361/16362 |
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10361-163622022-02-28T21:01:31Z Exploring Alzheimer's disease prediction with XAI in various neural network models Rahman, Quazi Ashikur Shad, Hamza Ahmed Asad, Nashita Binte Bakshi, Atif Zawad Mursalin, S.M Faiaz Parvez, Mohammad Zavid Reza, Md. Tanzim Department of Computer Science and Engineering, Brac University Early detection of AD Alzheimer's disease CNN model for AD detection Explainable artificial intelligence XAI LIME Neural networks (Computer science) Artificial intelligence Alzheimer's disease. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. Cataloged from PDF version of thesis. Includes bibliographical references (pages 50-52). Using a number of Neural Network Models, we attempt to explore and explain the prediction of Alzheimer's in patients in various stages of the disease, using MRI imaging data. Alzheimer's disease(AD) often described as dementia is one of the major neurological dysfunctionalities among humans and does not yet have a proven detection system; unless the nal stage symptoms of AD starts to be seen. It is observed that multimodal biological, imaging and other available neuropsychological data can ensure a high percentage of separation among (AD) patients from cognitively normal elders. However, they cannot surely predict or detect early enough that patients with early signs of mild cognitive impairment (MCI) can develop into Alzheimer's disease dementia in the future. But the research done till date shows a high probable detection rate in which they used the pattern classi er built on various longitudinal data. So in this paper we experimented with the existing Neural Network models to detect Alzheimer's disease in its early stage by classi cation techniques; and will be using a recent hybrid dataset in the process to have four separate classi cation in total. And also explored the exact region for which that speci c classi cation occurs for the patients, looking at the T1 weighted MRI scans from a hybrid dataset from Kaggle [21] using the LIME based XAI(Explainable Arti cial Intelligence) framework. For the Convolution Neural Network Models we are using Resnet50, VGG16 and Inception v3 and received 82.56%, 86.82%, 82.04% of categorical accuracy respectively. Quazi Ashikur Rahman Hamza Ahmed Shad Nashita Binte Asad Atif Zawad Bakshi S.M Faiaz Mursalin B. Computer Science 2022-02-28T04:38:11Z 2022-02-28T04:38:11Z 2021 2021-10 Thesis ID 18101577 ID 18101279 ID 18101622 ID 18101679 ID 18101508 http://hdl.handle.net/10361/16362 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 52 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Early detection of AD Alzheimer's disease CNN model for AD detection Explainable artificial intelligence XAI LIME Neural networks (Computer science) Artificial intelligence Alzheimer's disease. |
| spellingShingle |
Early detection of AD Alzheimer's disease CNN model for AD detection Explainable artificial intelligence XAI LIME Neural networks (Computer science) Artificial intelligence Alzheimer's disease. Rahman, Quazi Ashikur Shad, Hamza Ahmed Asad, Nashita Binte Bakshi, Atif Zawad Mursalin, S.M Faiaz Exploring Alzheimer's disease prediction with XAI in various neural network models |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021. |
| author2 |
Parvez, Mohammad Zavid |
| author_facet |
Parvez, Mohammad Zavid Rahman, Quazi Ashikur Shad, Hamza Ahmed Asad, Nashita Binte Bakshi, Atif Zawad Mursalin, S.M Faiaz |
| format |
Thesis |
| author |
Rahman, Quazi Ashikur Shad, Hamza Ahmed Asad, Nashita Binte Bakshi, Atif Zawad Mursalin, S.M Faiaz |
| author_sort |
Rahman, Quazi Ashikur |
| title |
Exploring Alzheimer's disease prediction with XAI in various neural network models |
| title_short |
Exploring Alzheimer's disease prediction with XAI in various neural network models |
| title_full |
Exploring Alzheimer's disease prediction with XAI in various neural network models |
| title_fullStr |
Exploring Alzheimer's disease prediction with XAI in various neural network models |
| title_full_unstemmed |
Exploring Alzheimer's disease prediction with XAI in various neural network models |
| title_sort |
exploring alzheimer's disease prediction with xai in various neural network models |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/16362 |
| work_keys_str_mv |
AT rahmanquaziashikur exploringalzheimersdiseasepredictionwithxaiinvariousneuralnetworkmodels AT shadhamzaahmed exploringalzheimersdiseasepredictionwithxaiinvariousneuralnetworkmodels AT asadnashitabinte exploringalzheimersdiseasepredictionwithxaiinvariousneuralnetworkmodels AT bakshiatifzawad exploringalzheimersdiseasepredictionwithxaiinvariousneuralnetworkmodels AT mursalinsmfaiaz exploringalzheimersdiseasepredictionwithxaiinvariousneuralnetworkmodels |
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1814307647573196800 |