AI in Healthcare contains all the elements that makes AI a hard problem. AI is hard because systems have to be able to cope with unexpected circumstances when solving perceptual, reasoning or planning problems (e.g. due to the diversity and variability of human nature). Moreover, while many AI systems can solve simple or restricted problems (e.g. in video games), they often fail when scaled up to more general settings and cannot operate with unusual situations and adjust accordingly. Thus, 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.
AI training in our Centre will generalise across a whole spectrum of AI application scenarios far beyond healthcare. Our Centre will train a new generation of PhD-level innovators. Tackling healthcare challenges requires learning how to bridge our understanding of the clinical language and methodologies, the regulatory, legal and ethical frameworks of healthcare with core AI technical skills. Our training outcomes are PhDs that have learned to move fluidly across the disciplinary AI/healthcare boundaries and can develop and implement deployable solutions. Crucially, we will empower our alumni through our unique training program to become independent actors in the highly regulated healthcare technology market and enable them to consolidate their impact through our NHS partnerships and globally through our international industrial partners so as to become part of the long-term legacy of our UKRI Centre.
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