View Proposal

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Proposer

Marta Vallejo

Title

Exploring Machine Learning Models to Uncover Pathways in ALS Pathogenesis Using Immunohistochemical Features

Goal

Description

This project invites students with a machine learning background to investigate the complexities of ALS pathogenesis by applying diverse machine learning models to an existing dataset. The study involves patients with a specific ALS-related mutation (C9orf72 HRE), whose data includes thousands of post-mortem tissue images with quantified immunohistochemical markers for microglial activation and protein misfolding. Using features extracted from a previous study, you will assess model performance and predictive accuracy using methods beyond the random forest approach originally applied. They will experiment with advanced algorithms such as support vector machines, gradient boosting, and neural networks to identify relationships within the dataset and to investigate which features or feature combinations best classify disease status and predict clinical outcomes. By implementing and comparing different machine learning models, students will gain insight into feature importance and model interpretability in biomedical data, with a focus on neurodegenerative disease applications. This project offers a hands-on opportunity to contribute to the understanding of ALS clinical heterogeneity and to test innovative model approaches, with the potential to inform future trial designs and therapeutic strategies for ALS.

Resources

The clinical support is provided by a clinical partner at the University of Aberdeen.

Background

Interest in the application of machine learning techniques in real clinical problems. Willingness to publish the results in a clinical journal.

Url

External Link

Difficulty Level

High

Ethical Approval

Full

Number Of Students

2

Supervisor

Marta Vallejo

Keywords

machine learning, medical data

Degrees

Bachelor of Science in Computer Science
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Software Engineering
Bachelor of Science in Statistical Data Science
BSc Data Sciences