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Research Objects for Palliative Care


Project Description

The project is supported by the University of Liverpool Doctoral Network in Future Digital Health, which is directed at creating and maintaining a community of AI health care professionals that can realise the benefits that AI can bring to Health Care. The vision is that of a world-class centre providing high-quality doctoral training within the domain of AI for Future Digital Health. Each available PhD project has been carefully co-created in collaboration with a health provider and/or a healthcare commercial interest so that the outcomes of the PhD research will be of immediate benefit. The network will be providing doctoral training, culminating in a PhD, in a collaborative environment that features, amongst other things, peer-to-peer and cohort-to-cohort based learning. On completion students will be well-placed to take up rewarding careers within the domain of AI and Digital Health.
With an ageing population, the need for palliative care in the UK is expected to increase by 42% by the year 2040. Palliative care, or end-of-life care improves the quality of care through expert symptom management, and by helping to align a patients’ care with their goals, values and priorities. Such interventions have a significant impact not only on the patient themselves during the final phase of their lives (which can often stretch from weeks to months) but also to their families and friends, and early involvement of palliative care for people with serious illness is associated with better outcomes for patients and families. Thus, technological innovations offer great potential to improve quality of life for people with palliative care needs. However, a challenging aspect of palliative care is the identification and prioritisation those patients in need of support, as well as establishing the appropriate care pathway for each individual. Currently this requires accessing numerous data sources to understand current conditions, treatment plans, related research protocols, etc.

The aim of this project is to explore how Research Objects can be used to model patients selected for Palliative Care. Research Objects are a linked-data formalism that brings together different types of distributed data, including workflows and process models, into a single, coherent and reusable component that tracks its provenance and evolves over time. Built upon knowledge modelling formalisms such as the W3C standards RDFS and OWL, they can be linked to the thousands of medical ontologies already in existence and used extensively by the medical community. This will also involve understanding the latest innovations in ontology and process model mapping, as well as tailoring these techniques specifically to the Palliative Care domain. Furthermore, this will involve working closely with sample, anonymised patient data.

The successful candidate will work in conjunction with the Marie Curie Hospice Liverpool, and to work with clinicians to understand the relevant data models for representing Palliative Care Pathways. Through their studies, the successful candidate will acquire a deep understanding of Ontology Engineering, and the Semantic Web, as well as gain an appreciation of distributed data, produced and coordinated by different, asynchronous agents (i.e. pieces of code that can act independently and proactively to find new knowledge and perform opportunistic tasks). The candidate should have coding experience in working with Java, and ideally data modelling experience.

To apply for this opportunity, please visit: https://www.liverpool.ac.uk/study/postgraduate-research/how-to-apply/

Funding Notes

This project is funded by the University of Liverpool Doctoral Network in Future Digital Health, successful students will receive a studentship of tuition fees paid at the Home/EU rate for 3.5 years and a stipend of £15,009 per annum for 3.5 years. In addition, students will have access to a research support fund of £1,000 per annum for purchasing equipment, consumables and conference costs co-managed by the academic supervisor. Applications from international students are welcomed, however suitable arrangements will need to be made for the difference between the Home/EU and international rate.

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