Project Abstract

The rise of artificial intelligence (AI) and machine learning has influenced increasing automation. AI is concerned with researching and developing methods which enable machines to perceive their environment through learning to carry out actions that can best achieve the defined goals. The continued evolution and potential application in many domains have given the view of machine learning as a general-purpose technology. In healthcare, improvements in machine learning have allowed AI to assist in many healthcare-related tasks. This technology has been applied to CT, MRI, X-ray, Ultrasound, and other imaging techniques. Aided by machine learning models, these techniques have evolved to detect tumours, lesions, fractures and tears. Machine learning has also been used to predict and diagnose the progression of neurodegenerative diseases, like Alzheimer’s disease, Parkinson?��s disease, and more. The primary aim of this project is to develop machine learning-based methods to determine the accuracy of biomarkers. The use of biomarkers for a safer alternative to invasive biopsy is a key aspect of this project. By focusing on cancer-derived extracellular vesicles in biofluids, identification of a set of biomarkers can be found and serve as indicators of the disease. To complete this task, understanding the role of extracellular vesicles, the process of selecting candidate biomarkers, and research into using a combination of biomarkers to increase the chances of an accurate diagnosis, is crucial. A predictive machine learning model will be developed to analyse the biomarkers. Statistical analysis will be performed to determine the accuracy of the model and the areas which can be tuned to provide a better result.

Keywords: Artificial Intelligence, Machine Learning, Healthcare

 Conference Details

Session: Presentation Stream 30 at Presentation Slot 8

Location: GH014 at Wednesday 8th 13:30 – 17:00

Markers: Sofya Lyakhova, Hoang Nga Nguyen

Course: MSc Advanced Computer Science, Masters PG

Future Plans: I’m looking for an industry placement