Health, medical and social AI research

Projects

Cancer detection (prostate, vulval, ovarian)

Researchers: Dr Hussein Al-Ali, Prof Silvia Cirstea, Dr Imran Ahmed, Dr Bassel Wattar, Fadi Alfhaily
In simple terms: AI helps find hidden signs of cancer that the human eye may miss.
Outcome: Earlier diagnosis means faster treatment and better survival.

Predicting early lung, pancreas and oesophageal cancer

Researcher: Prof Havovi Chichger
In simple terms: Using patterns in data, AI can flag people who may be at high risk of certain cancers.
Outcome: High-risk patients can be prioritised for testing, and, if required, receive treatment sooner.

Predicting surgical complications

Researcher: Prof Justin Stebbing
In simple terms: Before surgery, doctors can use AI to estimate who may need extra care.
Outcome: Fewer complications and safer operations, which can help improve patient recovery.

Emotion recognition for people with profound disabilities

Researcher: Prof Mick Finlay
In simple terms: AI can read facial cues and body signals, to help people who find communication challenging interact more effectively with caregivers.
Outcome: Better care, communication and wellbeing, which improves patient care and makes the health system more inclusive.

Making NHS workflows smarter

Researchers: Prof Sally Fowler Davis, Dr Tim Hayes, Dr Maria Wishart
In simple terms: AI can identify patterns in local staffing levels and composition, demand and skills in huge datasets pertaining to allied health professionals.
Outcome: Better NHS planning and more efficient services, which can save NHS time and money.

Find out more about our work making NHS workflows faster.

Mitochondrial imaging

Researcher: Prof Vicky MacRae
In simple terms: AI can help scientists understand how our cells create energy.
Outcome: Quicker development of effective treatments for mitochondrial diseases.

Eye modelling and synthetic datasets

Researcher: Prof Barbara Pierscionek
In simple terms: AI can help create realistic computer models of the eye.
Outcome: Better tools to diagnose eye conditions, especially when real patient data is limited.

Drug discovery using bioinformatics

Researchers: Prof Selim Cellek and the Fibrosis Research Group
In simple terms: AI can scan thousands of drug possibilities to spot the most promising ones.
Outcome: Faster, cheaper development of new medicines, meaning they could get to patients faster.

Autism screening

Researcher: Dr Shabnam Sadeghi Esfahlani
In simple terms: An AI-powered digital tool can support early autism assessment.
Outcome: Faster screening, offering the potential to reduce waiting lists for full diagnosis.

Neonatal jaundice detection

Researcher: Dr Ashim Chakraborty, Dr Cristina Luca, Prof Silvia Cirstea, Dr Ian van der Linde
In simple terms: A new AI tool can use ordinary smartphone images to non-invasively detect neonatal jaundice and identify at-risk babies sooner.
Outcome: Earlier intervention, reduced need for invasive testing, and improved screening access in low- and middle-income countries and regions with higher neonatal mortality rates.

Find out more about our work on neonatal jaundice detection.