Health data are rising rapidly. The growing influence of AI has yielded great prospects but also raised important questions about the future role of AI in relation to humans, which are critical to healthcare applications where humans are supposed to make clinical decisions. Can we trust the AI decisions? What is the best way to assess AI outcomes? – these are the key questions waiting for answers. The lack of research in this area has led to problems. Hence, there is a significant demand in addressing this shortage by training researchers to carry out research in this new dimension. To this end, HAIH will be a timely effort to fulfil these needs.
We envision a new research direction in AI for health to foster a transformative human centric paradigm, in which an emerging collaborative relationship between computers and humans will be created based on the ever-increasing power of AI. The computers will no longer just be used as tools, but instead act actively as a co-worker to offer sound, clear and evidence-based solutions to support clinicians and patients in clinical decision making and enhance clinical outcomes.
The research will focus on three specific research themes:
- Trusted Data: Uncertainty, risk and security aware modelling of health data that will handle randomly varying nonlinearities, uncertain and missing measurements, where new approaches to estimate risks and predict outcomes of clinical decision support for informed choice in the face of risk and uncertainty will be targeted. This will be joined by the research in a person-centric, decentralised and privacy preserving approach that enables verifiable evidences of patient controlled data in the care cycle with enhanced trusts among stakeholders and regulatory compliance.
- Trusted AI: Explainable and secure AI that will contribute to the trust in the clinical decisions recommended by AI by investigating innovative AI-based health solutions that are explainable, secure, trustworthy and acceptable by humans. This will involve training relation-preserving abstracted knowledge models to support compositional and explainable reasoning, and hence provide insight into the AI’s choices and robustness.
- Trust in Human Factors: Human centred AI design that will investigate human factors and identify barriers in clinical acceptance to support a transformative human & AI collaboration experience based on trusted AI and data in the context of healthcare.
3 studentships are available for 42 months. The fund will cover home tuition fee, stipend, travel and equipment.
The studentships will be part of the initial cohort of the Strathclyde Centre for Doctoral Training in Human Centric AI in Healthcare (HAIH). The newly established centre is led by Prof Feng Dong, and aims to deliver collaborative research in Health Technologies within the Technology & Innovation Zone Cluster at Glasgow City Innovation District. We will explore human centric AI as a key technology backbone in health, leveraging the participation of many key academics with a wide range of expertise in AI, digital health, uncertainty and risk modelling, prediction and security, which will significantly benefit the students in their path to become the next generation AI researchers in health. The centre is also supported by the research groups in 3 regional NHS boards in Scotland and 1 hospital in London, and is sponsored by leading industries of AI in health.
How to apply
Please email Professor Feng Dong if you would like to apply for this opportunity