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Artificial intelligence in the diagnosis of necrotising enterocolitis in newborns


Necrotising enterocolitis (NEC) is one of the most common diseases in neonates and predominantly affects premature or very-low-birth-weight infants. Diagnosis is difficult and needed in hours since the first symptom onset for the best therapeutic effects. Artificial intelligence (AI) may play a significant role in NEC diagnosis. A literature search on the use of AI in the diagnosis of NEC was performed. Four databases (PubMed, Embase, arXiv, and IEEE Xplore) were searched with the appropriate MeSH terms. The search yielded 118 publications that were reduced to 8 after screening and checking for eligibility. Of the eight, five used classic machine learning (ML), and three were on the topic of deep ML. Most publications showed promising results. However, no publications with evident clinical benefits were found. Datasets used for training and testing AI systems were small and typically came from a single institution. The potential of AI to improve the diagnosis of NEC is evident. The body of literature on this topic is scarce, and more research in this area is needed, especially with a focus on clinical utility. Cross-institutional data for the training and testing of AI algorithms are required to make progress in this area.


  • Only a few publications on the use of AI in NEC diagnosis are available although they offer some evidence that AI may be helpful in NEC diagnosis.

  • AI requires large, multicentre, and multimodal datasets of high quality for model training and testing. Published results in the literature are based on data from single institutions and, as such, have limited generalisability.

  • Large multicentre studies evaluating broad datasets are needed to evaluate the true potential of AI in diagnosing NEC in a clinical setting.

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Fig. 1: Clinical and radiographic features of necrotising enterocolitis.
Fig. 2: Flow diagram of the study selection process.


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We would like to thank Editage ( for English language editing.


This publication is partly supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement Sano No. 857533 and the International Research Agendas programme of the Foundation for Polish Science, co-financed by the European Union under the European Regional Development Fund.

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Authors and Affiliations



A.S. and J.S.-S. conceptualised and designed the review. K.W. performed literature search. All authors wrote and contributed to all sections. A.S. produced the final version and all authors approved the final version of the manuscript.

Corresponding authors

Correspondence to Arkadiusz Sitek or Joanna Seliga-Siwecka.

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Search strategy for narrative review.


(“artificial intelligence”[tiab] OR “artificial intelligences”[tiab] OR AI[tiab] OR “machine learning”[tiab] OR “machines learning”[tiab] OR “deep learning”[tiab] OR “decision tree”[tiab] OR “decision trees”[tiab] OR “neural network”[tiab] OR “neural networks”[tiab] OR “neural net”[tiab] OR “neural nets”[tiab] OR “medical image processing”[tiab] OR “Artificial Intelligence”[Mesh]) AND (“necrotizing enterocolitis”[tiab] OR NEC[tiab] OR “Enterocolitis, Necrotizing”[Mesh]).


(‘artificial intelligence’:ti,ab,kw OR ‘artificial intelligences’:ti,ab,kw OR ai:ti,ab,kw OR ‘machine learning’:ti,ab,kw OR ‘machines learning’:ti,ab,kw OR ‘deep learning’:ti,ab,kw OR ‘decision tree’:ti,ab,kw OR ‘decision trees’:ti,ab,kw OR ‘neural network’:ti,ab,kw OR ‘neural networks’:ti,ab,kw OR ‘neural net’:ti,ab,kw OR ‘neural nets’:ti,ab,kw OR ‘medical image processing’:ti,ab,kw OR ‘artificial intelligence’/exp) AND (‘necrotizing enterocolitis’:ti,ab,kw OR nec:ti,ab,kw OR ‘necrotizing enterocolitis’/exp).


“necrotizing enterocolitis”.

IEEE Xplore

(“artificial intelligence” OR “artificial intelligences” OR AI OR “machine learning” OR “machines learning” OR “deep learning” OR “decision tree” OR “decision trees” OR “neural network” OR “neural networks” OR “neural net” OR “neural nets” OR “medical image processing”) AND “necrotizing enterocolitis”.

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Sitek, A., Seliga-Siwecka, J., Płotka, S. et al. Artificial intelligence in the diagnosis of necrotising enterocolitis in newborns. Pediatr Res (2022).

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