Artificial intelligence for diagnosis/ disease stratification of NEC


NEC UK are supporting Stavros P. Loukogeorgakis MBBS BSc PhD FRCS(Paed)

on a collaborative/multicentre project aiming to assess the utility of artificial intelligence for the early/timely diagnosis and stratification of NEC.

Written by: Stavros P. Loukogeorgakis MBBS BSc PhD FRCS(Paed)

Necrotising Enterocolitis (NEC) is a bowel condition affecting up to 12% of premature newborn babies. It can have severe consequences with up to half the patients afflicted with this condition dying within the first year of life. Many others require prolonged, specialised care including surgery, antibiotics and nutritional support.


It can be very challenging to diagnose the disease as it can often present in a similar manner to other conditions. In particular, identifying early changes on X-ray imaging can be very difficult. Therefore, paediatric surgeons, neonatologists and radiologists require significant training and experience to diagnose NEC in a timely manner and treat it. Unfortunately, many hospitals around the country lack this particular expertise. As a consequence, there is delayed treatment, including transfer to a surgical centre for operative intervention, resulting in worse outcomes.

In order to address this, clinicians at Great Ormond Street Hospital (GOSH) are collaborating with the University College London Welcome/EPSRC Centre for Interventional and Surgical Sciences (UCL WEISS). The two teams are combining their clinical and technical expertise to conduct research into the use of artificial intelligence (AI) to diagnose NEC. We intend to design an AI algorithm that reviews X-ray images and clinical data to identify NEC earlier. It should empower other centres to identify the disease early without the presence of a specialist clinician and prompt timely transfer to a surgical centre for operative treatment. Furthermore, by harnessing the power of this technology we hope to develop more individualised and personalised therapeutic strategies for our patients. For example, it may determine ideal antibiotic treatment durations and also predict which babies may require earlier surgical intervention. Our team is very excited by the potential of the AI algorithm we are developing and, upon successful completion of our research, we aspire to implement it nationally in order to revolutionise the treatment of NEC.



Stavros P. Loukogeorgakis MBBS BSc PhD FRCS(Paed)

Associate Professor of Paediatric Surgery

Research and Teaching Department of Developmental Biology and Cancer

UCL Great Ormond Street Institute of Child Health

Consultant Neonatal and Paediatric Surgeon

Department of Specialist Neonatal and Paediatric Surgery (SNAPS)

Great Ormond Street Hospital for Children NHS Foundation Trust


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