Exploring Alzheimer's disease prediction with XAI in various neural network models

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.

Bibliografske podrobnosti
Main Authors:	Rahman, Quazi Ashikur, Shad, Hamza Ahmed, Asad, Nashita Binte, Bakshi, Atif Zawad, Mursalin, S.M Faiaz
Drugi avtorji:	Parvez, Mohammad Zavid
Format:	Thesis
Jezik:	English
Izdano:	Brac University 2022
Teme:	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.
Online dostop:	http://hdl.handle.net/10361/16362

Podobne knjige/članki

Bank loan prediction using machine learning
od: Mahottam, Parthosarothi, et al.
Izdano: (2023)

An ambient assisted living system for Alzheimer’s patients
od: Abedin, Minhajul, et al.
Izdano: (2023)

Emerging therapies of Alzheimer’s disease: a comprehensive review
od: Tasin, Md Abtahi
Izdano: (2023)

Efficacy of Rivastigmine in Alzheimer’s disease- A structured seview
od: Alim, Abdul
Izdano: (2023)

Exploring the intersection of machine learning and explainable artificial intelligence: An analysis and validation of ML models through XAI for intrusion detection
od: Rahman, Masroor, et al.
Izdano: (2023)

Gender-specific Rhabdomyolysis risk in Alzheimer’s disease patients receiving memantine: a pharmacovigilance study
od: Tabassum, Nadira
Izdano: (2024)

Knowledge of Alzheimer’s disease and its relationship with attitude towards genetic testing for the disease: a survey of the general public in Bangladesh
od: Chowdhury, Sariya Uzrat
Izdano: (2022)

A pharmacovigilance study to determine risk of mortality in male and female patients with Alzheimer's disease using Rivastigmine
od: Shehab, Habibul Mohsin
Izdano: (2024)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
od: Ifty, Md. Hasin Sarwar, et al.
Izdano: (2024)

Explainable AI (XAI) driven skin cancer detection using transformer and CNN based architecture
od: Radiah, Faiza, et al.
Izdano: (2024)

XOPSIS: an explainable AI method based on the order of preference by similarity to ideal solution
od: Rahman, Anika
Izdano: (2024)

Heart attack prediction using machine learning and XAI
od: Ahsan, Mumtahina
Izdano: (2023)

PDFGuardian: An innovative approach to interpretable PDF malware detection using XAI with SHAP framework
od: Rahman, Tahsinur, et al.
Izdano: (2023)

Role of protein’s and future treatment options for Alzheimer’s Disease
od: Islam, Md. Irfath
Izdano: (2023)

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

Review on: Contribution of nutrients to retard the progression of Alzheimer’s disease
od: Saha, Bithi Rani
Izdano: (2023)

Voice impersonation detection using LSTM based RNN and explainable AI
od: Barua, Kawshik, et al.
Izdano: (2022)

Comprehensive review on importance, challenges and future prospects of nanotechnology and combination therapy for Alzheimer’s disease
od: Ishrat, Nowshin
Izdano: (2024)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
od: Haque, Abid Hossain, et al.
Izdano: (2024)

Alzheimer's disease and marriage : an intimate account /
od: Wright, Lore K.
Izdano: (1993)

Signal detection of Rhabdomyolysis and death for galantamine: a pharmacovigilance study
od: Karmaker, Swastika
Izdano: (2024)

Progress of finding latent therapeutic activity of vaccine for Alzheimer’s disease
od: Hassan, Md. Muhtaz
Izdano: (2020)

Machine learning approach for ECG analysis and predicting different heart diseases
od: Tithi, Sushmita Roy, et al.
Izdano: (2019)

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
od: Farhan, Rafid, et al.
Izdano: (2024)

Glymphatic system: a pathway for managing endogenous metabolites in CNS
od: Tasneem, Sadia
Izdano: (2021)

Real time performance analysis on DDoS attack detection using machine learning
od: Suvra, Debashis Kar, et al.
Izdano: (2021)

Bio-similar drug development and accessible drugs in the market for the treatment of Alzheimer's Disease: Current status
od: Tamanna, Mst. Taskia
Izdano: (2023)

Biomarkers of Alzheimer’s disease: a hope for early diagnosis
od: Aziz, Farhin
Izdano: (2019)

Comparison of machine learning techniques to predict cardiovascular disease
od: Jaber, Mir Mohammad, et al.
Izdano: (2019)

Disease detection system of mango leaves
od: Islam, Sabrina, et al.
Izdano: (2024)

Detection and classification of Mango Leaf diseases utilizing convolutional neural network models
od: Ferdous, Md.Rubaiat, et al.
Izdano: (2024)

Prospective detection methods for Tau protein: an important biomarker for Alzheimer’s disease
od: Afra, Sumaiya
Izdano: (2022)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
od: Rafat, Md. Tasbi, et al.
Izdano: (2023)

The role of Artificial Intelligence (AI) in the detection and diagnosis of chronic diseases – a review
od: Zaman, Mumtahina
Izdano: (2022)

Marine compounds in the treatment of Alzheimer’s disease
od: Parveen, Sanjana
Izdano: (2022)

An efficient deep learning approach for detecting Alzheimer’s disease using brain images
od: Sani, Mehedi Hasan, et al.
Izdano: (2022)

Application of microRNA (miRNA) in Alzheimer’s Disease (AD)
od: Halim, Rabea
Izdano: (2022)

Gene editing for neurodegenerative diseases-A review
od: Sharna, Anika Islam
Izdano: (2023)

Interpretable MOOC dropout prediction using different Ensemble Methods and XAI
od: Khan, Labib Hasan, et al.
Izdano: (2023)

Personalization in federated recommendation system using SVD++ with explainability
od: Patwary, Kabbya Kantam, et al.
Izdano: (2022)