Optimization of Diagnosis and Treatment for AMD Based on Machine Learning

1) Brief description of the context of the research including potential impact

The PhD will employ advanced machine learning tool to optimize the diagnosis accuracy and treatment strategy for Age-related macular degeneration (AMD). This research would promote the medical AI application in the ophthalmology.

2) Aims and objectives

AMD is the leading cause of irreversible blindness in the UK, Europe, and North America. In the UK alone, nearly 200 people develop the blinding forms of AMD every single day. Much of the visual loss in AMD occurs due to the development of choroidal neovascularization (CNV) - so called wet or neovascular AMD. In recent years, this condition can be successfully treated with pharmacotherapies that block vascular endothelial growth factor (VEGF). Unfortunately, patients receiving this treatment require intraocular injections on a monthly basis over many years. In order to reduce the burden on patients, while preventing irreversible sight loss, a number of variable treatment regimens have evolved.

3) Novelty of the research methodology

With the boosting development of medical AI research, deep learning offers strong support in disease diagnosis due to the representation capability. By looking into the deep learning core principle, we could explore the reliability and interpretability of AI in ophthalmology. Simultaneously unsupervised learning can identify distinct groups and their trajectories of decline supporting precision assignment of individuals to the right treatment regime for them. The PhD will develop such algorithms and methods and work with clinicians to enable application on real-world datasets.

4) Alignment to EPSRC's strategies and research areas

The PhD's work fits primarily in the research themes of "Healthcare Technologies" and "Information and communication technologies", and within the Research areas of "Artificial Intelligence Technologies" and "Medical Imaging".

5) Any companies or collaborators involved

Moorfields Eye Hospital NHS Foundation Trust.

The critical mass of scientists and engineers that i4health will produce will ensure the UK's continued standing as a world-leader in medical imaging and healthcare technology research. In addition to continued academic excellence, they will further support a future culture of industry and entrepreneurship in healthcare technologies driven by highly trained engineers with deep understanding of the key factors involved in delivering effective translatable and marketable technology. They will achieve this through high quality engineering and imaging science, a broad view of other relevant technological areas, the ability to pinpoint clinical gaps and needs, consideration of clinical user requirements, and patient considerations. Our graduates will provide the drive, determination and enthusiasm to build future UK industry in this vital area via start-ups and spin-outs adding to the burgeoning community of healthcare-related SMEs in London and the rest of the UK. The training in entrepreneurship, coupled with the vibrant environment we are developing for this topic via unique linkage of Engineering and Medicine at UCL, is specifically designed to foster such outcomes. These same innovative leaders will bolster the UK's presence in medical multinationals - pharmaceutical companies, scanner manufacturers, etc. - and ensure the UK's competitiveness as a location for future R&D and medical engineering. They will also provide an invaluable source of expertise for the future NHS and other healthcare-delivery services enabling rapid translation and uptake of the latest imaging and healthcare technologies at the clinical front line. The ultimate impact will be on people and patients, both in the UK and internationally, who will benefit from the increased knowledge of health and disease, as well as better treatment and healthcare management provided by the future technologies our trainees will produce.

In addition to impact in healthcare research, development, and capability, the CDT will have major impact on the students we will attract and train. We will provide our talented cohorts of students with the skills required to lead academic research in this area, to lead industrial development and to make a significant impact as advocates of the science and engineering of their discipline. The i4health CDT's combination of the highest academic standards of research with excellent in-depth training in core skills will mean that our cohorts of students will be in great demand placing them in a powerful position to sculpt their own careers, have major impact within our discipline, while influencing the international mindset and direction. Strong evidence demonstrates this in our existing cohorts of students through high levels of conference podium talks in the most prestigious venues in our field, conference prizes, high impact publications in both engineering, clinical, and general science journals, as well as post-PhD fellowships and career progression. The content and training innovations we propose in i4health will ensure this continues and expands over the next decade.