Detection of early stages of Parkinson's disease by analyzing fMRI data and machine learning approaches

Detection of early stages of Parkinson's disease by analyzing fMRI data and machine learning approaches

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.

Dettagli Bibliografici
Autori principali:	Neehal, Ahmed Hasin, Azam, Md. Nura, Islam, Md. Sazzadul, Hossain, Md. Ishrak
Altri autori:	Parvez, Mohammad Zavid
Natura:	Tesi
Lingua:	English
Pubblicazione:	Brac University 2020
Soggetti:	Functional imaging Parkinson's disease fMRI Voxel intensity Machine learning SVM classifier STFT
Accesso online:	http://hdl.handle.net/10361/13884

Documenti analoghi

Comparison of different CNN architectures for brain tumor detection using fMRI
di: Mashiat, Afsara, et al.
Pubblicazione: (2021)

Brain image fMRI data classification and graphical representation of visual object
di: Tasneem, Nazifa Afroza, et al.
Pubblicazione: (2019)

Detection of prodromal parkinson’s disease with fMRI data and deep neural network approaches
di: Shahriar, Farhan, et al.
Pubblicazione: (2021)

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
di: Tanvir, Farhan, et al.
Pubblicazione: (2024)

Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
di: Ashraf, S.M. Nabil, et al.
Pubblicazione: (2021)

Epileptic seizure detection by exploiting EEG signals using different decomposition techniques and machine learning approaches
di: Karim, Rezwanul, et al.
Pubblicazione: (2019)

Impact of Lifestyle on the Disease Progression of Parkinson’s
di: Annee, Israt Jahan
Pubblicazione: (2023)

fMRI
Pubblicazione: (2013)

Visual object classification from fMRI data
di: Newaz, Syed Mishar, et al.
Pubblicazione: (2022)

Diagnostic biomarkers of Parkinson’s disease: The present and the future
di: Ferdous, Labiba
Pubblicazione: (2023)

Review on: the mechanism and function of Glia in parkinson's disease
di: Abedin, Khondokar Mezbahul
Pubblicazione: (2023)

Detection of Parkinson’s disease from Neuro-imagery using deep neural network with transfer learning
di: Asaduzzaman, et al.
Pubblicazione: (2021)

Sentiment analysis for Bengali newspaper headlines
di: Hossain, Mohammad Samman, et al.
Pubblicazione: (2017)

Application of deep learning in MRI classification of Schizophrenia
di: Joyee, Ramisa Fariha, et al.
Pubblicazione: (2024)

Parkinson's disease in Bangladesh: An evaluation of the public knowledge and awareness
di: Chowdhury, Amal
Pubblicazione: (2024)

Parkinson’s disease and COVID-19: treatment and patient management during a pandemic
di: Afsana, Nourin
Pubblicazione: (2022)

Treatment options of Parkinson’s disease: How far we are from the cure?
di: Afreen, Nuraia
Pubblicazione: (2021)

A look into parkinson’s disease and the implications of gene therapy as a novel clinical approach
di: Islam, Md. Rakibul
Pubblicazione: (2023)

Early detection of parkinson’s disease using image processing and artificial neural network
di: Rumman, Mosarrat, et al.
Pubblicazione: (2018)

Use of machine learning and IoT for monitoring and tracking of livestock
di: Aunindita, Rudaba Farhin, et al.
Pubblicazione: (2023)

Automated system for detecting jute plant disease using image processing and machine learning integrated with mobile application
di: Joyee, Faiza Nuzhat, et al.
Pubblicazione: (2016)

Symptom analysis of Parkinson disease using SVM-SMO and Ada-Boost classifiers
di: Billah, Muhtasim
Pubblicazione: (2014)

Isolation of pathogens from tracheal infection of intensive care unit admitted patients and analysis of antibiotic susceptibility
di: Haque, Sabrina
Pubblicazione: (2021)

Semantic segmentation of tumor from 3D Structural MRI using U-Net Autoencoder
di: Farzana, Maisha, et al.
Pubblicazione: (2021)

In-depth analysis of deep learning architectures for brain tumor classification in MRI scans
di: Haque, Hossain MD. Hasibul, et al.
Pubblicazione: (2024)

Autism detection based on MRI images using Deep Learning
di: Mostafa, Sadab, et al.
Pubblicazione: (2023)

A federated learning approach for detecting Parkinson’s disease through privacy preserving by blockchain
di: Dipro, Sumit Howlader, et al.
Pubblicazione: (2022)

Design and implementation of a F-Commerce restaurant application
di: Khan, Mushfiquzzaman, et al.
Pubblicazione: (2018)

Improvisation of Magnetic Resonance Imaging (MRI) with development and feasible evaluation of fiber optic sensors: a survey
di: Shabnam, Farzana, et al.
Pubblicazione: (2018)

Impact of manufacturing industry specific FDI inflow on economic growth
di: Mubde, Mutasim Billah
Pubblicazione: (2018)

Investigating the link between Cardiovascular diseases and neurodegenerative disorders
di: Dey, Manashi
Pubblicazione: (2024)

Memoirs of F.L.I.T.
di: Yesmin, Samiya
Pubblicazione: (2017)

Email classification and meeting scheduling using classifier algorithm
di: Khan, Behroz Newaz, et al.
Pubblicazione: (2017)

Stress detection for visually impaired people using EEG signals based on extracted features from time-frequency domain
di: Sultana, Samia
Pubblicazione: (2023)

An Efficient deep learning approach to detect Brain Tumor using MRI images
di: Islam, Annur Tasnim, et al.
Pubblicazione: (2022)

Induced pluripotent stem cells: a novel tool for modelling and treating Parkinson’s disease
di: Tanin, Nahid Sultana
Pubblicazione: (2022)

Gender classification in Bangla language using deep learning-based voice analysis
di: Hakim, Talukder Juhaer, et al.
Pubblicazione: (2024)

Multi-classification based Alzheimer's disease detection with comparative analysis from brain MRI scans using deep learning
di: Kabir, Azmain, et al.
Pubblicazione: (2022)

Pending Issue of design coordination for 1F-3F construction
di: Brac University
Pubblicazione: (2023)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
di: Shourin, Bushra, et al.
Pubblicazione: (2018)