A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.
| Principais autores: | , , , |
|---|---|
| Outros Autores: | |
| Formato: | Tese |
| Idioma: | English |
| Publicado em: |
Brac University
2022
|
| Assuntos: | |
| Acesso em linha: | http://hdl.handle.net/10361/17568 |
| id |
10361-17568 |
|---|---|
| record_format |
dspace |
| spelling |
10361-175682022-11-15T21:01:43Z A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain Dipro, Sumit Howlader Islam, Mynul Nahian, Md.Abdullah Al Azad, Moonami Sharmita Chakrabarty, Amitabha Reza, Md. Tanzim Department of Computer Science and Engineering, Brac University Parkinson’s disease Federated learning Healthcare Blockchain Privacy preserving Neural networks (Computer science) Machine learning Computer algorithms Data encryption (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. Cataloged from PDF version of thesis. Includes bibliographical references (pages 55-59). Parkinson’s disease is a degenerative ailment caused by the loss of nerve cells in the brain region known as the Substantia Nigra, which governs movement. These nerve cells die or deteriorate, rendering them unable to produce an essential neurotransmitter called dopamine. The loss of dopamine in the basal ganglia precludes normal function when the substantia nigra neurons are harmed in large numbers. This results in the motor symptoms of Parkinson’s disease, including tremor, rigidity, decreased balance, and lack of spontaneous movement. For the detection of PD, traditional machine learning algorithms have been used in many research papers. However, traditional ML algorithms always put a risk on the sensitivity of patients’ data privacy. This research proposes a novel approach to detect PD by preserving privacy and security through Blockchain-based Federated Learning. FL may train a single algorithm across numerous decentralized local servers as an improved version of the ML approach instead of trading gradient information. Blockchain can be effectively used to preserve privacy and secure transactions (i.e., gradient) between local and central servers. The proposed model has been tested and evaluated by using three CNN models (VGG19, VGG16 & InceptionV3) in this research, and within these models VGG19 has the best accuracy of 97%. The result demonstrates that this model is very accurate for detecting PD by preserving one’s privacy and security through Blockchain-based Federated Learning. Sumit Howlader Dipro Mynul Islam Md.Abdullah Al Nahian Moonami Sharmita Azad B. Computer Science and Engineering 2022-11-15T05:23:02Z 2022-11-15T05:23:02Z 2022 2022-05 Thesis ID 18101154 ID 18101155 ID 17301102 ID 16201039 http://hdl.handle.net/10361/17568 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. 59 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Parkinson’s disease Federated learning Healthcare Blockchain Privacy preserving Neural networks (Computer science) Machine learning Computer algorithms Data encryption (Computer science) |
| spellingShingle |
Parkinson’s disease Federated learning Healthcare Blockchain Privacy preserving Neural networks (Computer science) Machine learning Computer algorithms Data encryption (Computer science) Dipro, Sumit Howlader Islam, Mynul Nahian, Md.Abdullah Al Azad, Moonami Sharmita A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Dipro, Sumit Howlader Islam, Mynul Nahian, Md.Abdullah Al Azad, Moonami Sharmita |
| format |
Thesis |
| author |
Dipro, Sumit Howlader Islam, Mynul Nahian, Md.Abdullah Al Azad, Moonami Sharmita |
| author_sort |
Dipro, Sumit Howlader |
| title |
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| title_short |
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| title_full |
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| title_fullStr |
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| title_full_unstemmed |
A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain |
| title_sort |
federated learning approach for detecting parkinson’s disease through privacy preserving by blockchain |
| publisher |
Brac University |
| publishDate |
2022 |
| url |
http://hdl.handle.net/10361/17568 |
| work_keys_str_mv |
AT diprosumithowlader afederatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT islammynul afederatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT nahianmdabdullahal afederatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT azadmoonamisharmita afederatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT diprosumithowlader federatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT islammynul federatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT nahianmdabdullahal federatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain AT azadmoonamisharmita federatedlearningapproachfordetectingparkinsonsdiseasethroughprivacypreservingbyblockchain |
| _version_ |
1814308148273479680 |