| EPSRC Reference: |
EP/S023283/1 |
| Title: |
UKRI Centre for Doctoral Training in Artificial Intelligence for Healthcare |
| Principal Investigator: |
Faisal, Professor A |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Computing |
| Organisation: |
Imperial College London |
| Scheme: |
Centre for Doctoral Training |
| Starts: |
01 April 2019 |
Ends: |
30 September 2027 |
Value (£): |
8,196,302
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| EPSRC Research Topic Classifications: |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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07 Nov 2018
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UKRI Centres for Doctoral Training AI Interview Panel V – November 2018
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Announced
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Summary on Grant Application Form |
The UKRI CDT in Artificial Intelligence (AI) for Healthcare will be the world's leading centre for PhD training of the next-generation innovators in AI applied to Healthcare. There is a unique role for AI in healthcare by providing more accurate decisions faster while reducing cost and suffering across society. AI in healthcare needs and drives current AI research avenues such as interpretable AI, privacy-preserving learning, trust in AI, data-efficient learning and safety in autonomy. These are key due to the immediate impact on life and health for users depending on AI for healthcare support. Healthcare applications require many AI specialists that can apply their skills in this heavily regulated domain. To address this need, we propose to train in total 90+ PhD students including 16 clinical PhD Fellows in five cohorts of 18+ PhDs, which will establish a new generation of cognitively diverse AI researchers with backgrounds ranging from computer science, psychology to design engineering and clinical medicine.
The CDT focus areas arise from our early engagement in AI research and collaboration with clinicians, partnered technology companies and patient organisations, reflecting the healthcare areas of the UK industrial strategy. The Centre is grouped into 4 complementary healthcare themes and 4 cross-cutting AI expertise streams. The 4 healthcare themes are:
(1) Productivity in Care: making healthcare provision more efficient and effective by increasing the productivity of doctors and nurses;
(2) Diagnostics & Monitoring: developing AI-based diagnostics & monitoring that can detect disease earlier and monitor health with more precision;
(3) Decision support systems: AI-based decision support systems that will support e.g. freeing up doctors' time to focus on the patient or can accelerate the development of novels drugs and treatments and empowering patients to be active agents within the decision-making by explaining, and
(4) Biomedical discovery: driven by AI that accelerates drug discovery and linking genome, microbiome and environment data to discover novel disease mechanisms and treatment pathways.
The themes are linked by 4 cross-cutting AI expertise streams:
a. Perceptual AI technology enables to perceive, structure, and recognise from sensory data clinically relevant information.
b. Cognitive AI technology mimics the reasoning, i.e. cognitive process, of healthcare specialists.
c. Assistive AI technology supports clinicians with decision making as well as patients directly
d. Underpinning AI technologies are driving factors for clinical and patient-focused AI innovations and will be enabling AI methodologies to operate beyond the currently possible.
Our unique cohorts will benefit from an integrated training program and co-creation process with industry and patient organisations. PhD training is split into three phases that provide underpinning skill training (Foundation phase), research training (Research Phase) and finally drive PhD impact (Impact phase). During the Impact phase, the students will either
(1) commercialising their research through a mentored start-up route (incubator partners),
(2) deploying their technology in a clinical trial (two NIHR biomedical research centre (BRC) partners), or
(3) testing their work in person through an NHS honorary contract (three NHS trusts as partners).
Bespoke training will be created, such as AI bias & ethics, security, trust, inclusivity, differential privacy, transparency, accessibility and usability, service design, global inclusivity, healthcare treatments, clinical statistics and data regulation, Healthcare technology regulation, and technology commercialisation.
We offer an exit Strategy (month 9-12) through a master's degree. The centre will place special emphasis on research that explores diversity in AI for healthcare research, including services to underserved communities and minority-specific care requirements.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.imperial.ac.uk |