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Developing artificial intelligence assistants to support condition monitoring, activation measurement and information access for patients with chronic health conditions

  • Full or part time
  • Application Deadline
    Monday, April 01, 2019
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

Current evidence suggests that for many chronic health conditions, treatment adherence rates are sub-optimal. Patients often lack the knowledge, skills and confidence (referred to as ‘patient activation’) to effectively manage complex conditions, and may be reluctant to report non-adherence to their clinicians. This has a severe impact on health outcomes and treatment costs. This project will bring together expertise in Artificial Intelligence (AI), Human-Computer Interaction (HCI), and Healthcare to explore the use of home-based AI assistants for monitoring and improving treatment adherence and ‘patient activation’ levels.

The successful candidate will investigate ways in which accountable, responsible and transparent AI assistants can be used to engage patients in human-to-device conversation about their condition, and capture adherence and activation data that can be used to personalise and improve their treatment. The project will also explore how AI can be used to provide tailored information to improve knowledge, skills, confidence and adherence.

The application of AI in healthcare contexts gives rise to societal and public policy issues which will be explored as part of the research. For example, while AI innovations may benefit health outcomes and treatment costs, the replacement of human professional judgment is likely to raise important ethical issues, including the potential for AI to make erroneous decisions.

The project will explore the potential of AI for shifting one-size-fits-all treatments and interventions towards more personalised approaches, with patients put in control of their self-management, supporting their independence, and recognising their individual needs through human-to-AI interaction. This will offer the potential to gather information that that is not captured and utilised in routine clinical practice, providing an exciting opportunity to improve the specificity of the patient interaction – even above the level of direct interaction with clinicians, and to increase the likelihood that individual barriers for self-management can be overcome.

This project is associated with the UKRI CDT in Accountable, Responsible and Transparent AI (ART-AI), which is looking for its first cohort of at least 10 students to start in September 2019. Students will be fully funded for 4 years (stipend, UK/EU tuition fees and research support budget). Further details can be found at: http://www.bath.ac.uk/research-centres/ukri-centre-for-doctoral-training-in-accountable-responsible-and-transparent-ai/.

Desirable qualities in candidates include intellectual curiosity, a strong background in maths and programming experience.

Applicants should hold, or expect to receive, a First Class or good Upper Second Class Honours degree. A master’s level qualification would also be advantageous.

Informal enquiries about the project should be directed to Dr Simon Jones: .

Enquiries about the application process should be sent to .

Formal applications should be made via the University of Bath’s online application form for a PhD in Computer Science: https://samis.bath.ac.uk/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUCM-FP01&code2=0013

Start date: 23 September 2019.

Funding Notes

ART-AI CDT studentships are available on a competition basis for UK and EU students for up to 4 years. Funding will cover UK/EU tuition fees as well as providing maintenance at the UKRI doctoral stipend rate (£15,009 per annum for 2019/20) and a training support fee of £1,000 per annum.

We also welcome all-year-round applications from self-funded candidates and candidates who can source their own funding.

How good is research at University of Bath in Computer Science and Informatics?

FTE Category A staff submitted: 24.00

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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