Healthcare systems are dealing with resource constraints on a massive scale, and current AI efforts are not pushing the envelope fast enough. A robust, safe and trusted AI system that can tackle early prediction, diagnosis and disease prevention could transform medicine, and that’s what we aim to do with CHAI Hub."Dr Hana Chockler
06 February 2024
King's part of £80 million boost in AI research to deliver revolutionary new technologies
Nine research hubs across the UK will help underpin the country’s commitment to leading AI research, innovation and ethical deployment.
Scientists from the Department of Informatics, Department of Engineering and School of Cancer and Pharmaceutical Sciences have been selected to take part in two of nine new artificial intelligence research hubs set up to empower researchers to tackle society’s pressing challenges with the help of AI.
Established in partnership with the University of Edinburgh and universities across the UK, the Causality in Healthcare AI with Real Data (CHAI) Hub will use funding from the Engineering and Physical Sciences Research Council (EPSRC) to explore how AI can improve healthcare outcomes for patients.
The AI Hub for Productive Research and Innovation in Electronics (APRIL) on the other hand, also in partnership with the University of Edinburgh, will develop AI tools to accelerate the development of key components necessary to build faster, cheaper, greener and overall, more efficient electronics. The hub will develop AI-based solutions to engineer and optimise new semiconductor materials, complex microchip designs and system architectures.
AI has increasingly been deployed in healthcare and hospital settings, playing a key role in diagnosis and even in patient-facing roles with vulnerable young people. However, current systems that are used in situations like these are typically narrow in scope.
These types of software focus primarily on revealing correlations between the input data they have been trained on, e.g. images of early onset breast cancer, and a variation of different outputs, like assessing if someone has a tumour. What they don’t know is the causal relationship between interventions and outcomes, whether a particular type of medication or surgery is likely to remove the negative impact of that tumour for an individual with a particular medical history.
By developing novel methods to identify and account for causal relationships in complex data sets reflective of an individual’s current medical status, CHAI Hub hopes to predict outcomes of medical treatments and help build personalised treatments for patients.
Dr Hana Chockler, Reader in Computer Science and King’s lead in the hub, explains “It’s clear that healthcare systems are dealing with resource constraints on an enormous scale, and while the AI integration in the healthcare system to date has promised to ease some of that, it’s not moving fast enough.
“By implementing causal AI we can provide an expert hand to front line clinicians in their day-to-day. We can present a formal picture of the effects of certain kinds of treatment on a patient, assess the likelihood of specific outcomes, and even estimate potentially dangerous 'what-if' scenarios. A robust, safe and trusted AI system that can tackle early prediction, diagnosis and disease prevention could transform medicine, and that’s what we aim to do with CHAI Hub.”
The CHAI Hub will enable multidisciplinary activities across faculties, Universities and the UK, and as such will provide new avenues of exploring health care data in an unprecedented way."Professor Anita Grigoriadis
While healthcare is a uniquely challenging environment with its complex and often unstructured sets of data from patient records and on-ward diagnoses, the CHAI hub team hope that the causal AI solutions they develop will be generic and therefore transplanted into areas like economics and finance with minor modifications.
Electronic devices are integral components of the computing and communication infrastructure underpinning modern life. The amount of data that is created, analysed and stored is increasing exponentially year on year, with global forecasts suggesting that this number will reach 181 zettabytes by 2025 – roughly ninety times the amount of 2010.
As computing demands continue to escalate, it is becoming increasingly crucial to develop energy-efficient, compact, and highly functional electronic components that can be used to create information processing systems that meet the challenges of an energy and security conscious world.
Data, and our capacity to transform it into meaningful and actionable intelligence, is what keeps the modern world turning – from developing new personalised medical treatments to inventing new technologies to enable the transition to a Net Zero economy. That’s why engineering information processing systems that consume less energy, prioritize security, and remain cost-efficient is a societal imperative."Professor Bipin Rajendran
As Professor Bipin Rajendran, co-lead on the ‘Device Design’ theme within APRIL, explains “Data, and our capacity to transform it into meaningful and actionable intelligence, is what keeps the modern world turning – from developing new personalised medical treatments to inventing new technologies to enable the transition to a Net Zero economy. That’s why engineering information processing systems that consume less energy, prioritize security, and remain cost-efficient is a societal imperative.
“My role within the hub will be to co-lead the theme on developing AI-based methods that can be used to create new electronic devices that can meet these challenges with optimum performance and yield, forming a cornerstone of the computing infrastructure of the future.”
These hubs will deliver revolutionary AI innovations and tools in sectors from healthcare to energy, smart cities and environment. They will achieve this by solving key challenges and improving our understanding of AI helping to drive the increased productivity and economic growth promised by this technology.”Professor Charlotte Deane, Executive Chair of the Engineering and Physical Sciences Research Council
In addition to CHAI Hub and APRIL, four hubs will explore how AI can be applied to accelerate the use of AI in areas such as cybersecurity, while three of the hubs will address the mathematics and computational research which is foundational to creating new AI systems.
Professor Charlotte Deane, Executive Chair of EPSRC, said “Artificial intelligence is already transforming our world. EPSRC supports world-leading research to unlock its potential and ensure it is developed and used in an ethical and responsible way. Long-term research funding has led to revolutionary advancements that have made AI a powerful tool for many applications.
“These hubs will deliver revolutionary AI innovations and tools in sectors from healthcare to energy, smart cities and environment. They will achieve this by solving key challenges and improving our understanding of AI helping to drive the increased productivity and economic growth promised by this technology.”