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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 8

Fine Tuning of an Ensemble of Classification Models Using Random Grid Search Parameters for a model are learned during the training while hyperparameters are set to control the implementation of the model. Grid-search is a technique used to find the optimal hyperparameters for a model. Ensemble learning involves training multiple models and combining the diverse […]

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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 7

Create a Web-based Application using XGBoost The implementation uses six features which are important to classify the stages of the disease and XGBoost to develop the web-based application. The features are CDRSB, Alzheimer’s Disease Assessment Scale (ADAS11), Rey Auditory Verbal Learning Test (RAVLT) immediate, MRI of whole brain and age of the subject at the […]

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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 6

Build a Classification Model using Tree-Based Algorithms In this implementation, selected features to build classification model include subject’s education, gender, age and a small list of biomarkers as discussed in different studies (Li et al., 2017), (Goyal et al., 2018), (Azvan et al., 2018). The biomarkers are cognitive tests such as Clinical Dementia Rating Sum […]

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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 5

Build a Classification Model using Monthly Changes in Radiology Imaging and Clinical Data Multiple studies such as (Lahmiri and Shmuel, 2018) and (Zhang and Sejdi´c, 2019) typically apply various machine learning algorithms to find the best model which correctly classifies stages of Alzheimer’s disease. In this implementation, features are selected based on two papers ((Goyal […]

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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 4

Implementation, Evaluation and Results of Alzheimers Disease Progression Models and Development of Web-based Application Introduction There are few conditions and perquisites for building classification models e.g., sample size of data, type of data, correlation, number of classes and type of problem. The studies suggest building multiple models and select the model with the best performance […]

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Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 3

Scientific Methodology and Architecture Design Introduction Alzheimer’s disease typically progresses gradually in stages namely normal, mild cognitive impairment (MCI) and dementia. The project represents an end-to-end functional approach to implement machine learning techniques and develop a web application. Alzheimer’s disease methodology (an adaptation of Knowledge Discovery in Databases (KDD) process) is applied to complete the […]

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Data Analysis Resources Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 2

Literature Review of Alzheimer’s Disease Progression Introduction This section discusses the papers published between 2004 and 2019 regarding Alzheimer’s disease progression. It starts by reviewing the application of machine learning on radiology images followed by different tests that are used to measure the clinical stage of the progression. This post is a continuation from this […]

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Data Analysis Resources Machine Learning

Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data – Part 1

“Classification of Alzheimer’s Disease Stages using Radiology Imaging and Longitudinal Clinical Data” is the topic of my final year project as part of my MSc in Data Analytics. I am publishing the technical report in full. Please let me know if you have any questions. The report and code are available from this GitHub repository. […]