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Proposer
Marta Vallejo
Title
Deep Learning-based Characterisation of Protein Aggregation in amyotrophic lateral sclerosis (ALS) - Collaboration with University of Aberdeen
Goal
Gaining understanding of real research of neurodegenerative diseases using deep/machine learning. A final journal/conference publication is expected if results are of enough quality.
Description
Amyotrophic lateral sclerosis (ALS) is a rapidly debilitating neurodegenerative disease that affects motor neurons. Patients develop progressive muscle weakness, leading to death due to respiratory failure, which typically occurs after 3–5 years of symptom onset. ALS affects 1.75 – 3 out of 100,000 individuals per year. The existence of protein aggregates (TDP-43) in affected motor neurons is still a poorly understood hallmark. This project aims to increase the understanding of these structures by using a real clinical Immunohistochemistry dataset collected by the University of Edinburgh and applying different machine learning techniques to extend the understanding of the TDP-43 aggregates at an individual level. This project aims at characterising in more detail how distinct species of aggregates and their distribution are presented in different cells and different patients.
Resources
A real clinical dataset gathered by our clinical collaborators.
Background
Interest in the topic and techniques. Good programming skills. Willingness to learn. Interest in healthcare.
Url
Difficulty Level
High
Ethical Approval
Full
Number Of Students
3
Supervisor
Marta Vallejo
Keywords
machine learning, deep learning, medical imagen
Degrees
Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Bachelor of Science in Statistical Data Science