R
Robert Mark Beattie
Researcher at Boston Children's Hospital
Publications - 114
Citations - 2830
Robert Mark Beattie is an academic researcher from Boston Children's Hospital. The author has contributed to research in topics: Inflammatory bowel disease & Medicine. The author has an hindex of 25, co-authored 100 publications receiving 2427 citations. Previous affiliations of Robert Mark Beattie include Southampton General Hospital & Guy's Hospital.
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Journal ArticleDOI
Mucosal healing and a fall in mucosal pro-inflammatory cytokine mRNA induced by a specific oral polymeric diet in paediatric Crohn's disease.
J. M. E. Fell,M Paintin,F Arnaud-Battandier,Robert Mark Beattie,A Hollis,P. Kitching,A. Donnet-Hughes,Thomas T. MacDonald,John A. Walker-Smith +8 more
TL;DR: Although enteral nutrition is a recognized form of treatment for intestinal Crohn’s disease, there are persisting problems with feed palatability and only limited data as to its mode of action.
Journal ArticleDOI
Polymeric nutrition as the primary therapy in children with small bowel Crohn's disease.
Robert Mark Beattie,E. J. Schiffrin,A. Donnet-Hughes,A. C. Huggett,P Domizio,Thomas T. MacDonald,John Walker-Smith +6 more
TL;DR: This work has shown that polymeric (whole protein) diets are as effective as semi‐elemental and elemental formulae for the induction of remission in small bowel Crohn's disease in adults.
Journal ArticleDOI
Neonatal short bowel syndrome as a model of intestinal failure: Physiological background for enteral feeding
Olivier Goulet,Joanne Olieman,Janusz Ksiazyk,J. Spolidoro,D. Tibboe,H. Köhler,R. Vural Yagci,J. Falconer,George K. Grimble,Robert Mark Beattie +9 more
TL;DR: The physiological principles and nutritional management, including the type of diet and route of delivery and Perspectives in optimizing intestinal adaptation and reducing the consequences of small intestinal bacterial overgrowth are discussed.
Journal ArticleDOI
A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases.
Imogen S. Stafford,M. Kellermann,Enrico Mossotto,Robert Mark Beattie,Ben D. MacArthur,Sarah Ennis +5 more
TL;DR: The field may benefit from adopting a best practice of validation, cross-validation and independent testing of ML models, and progression to more complex predictive models may be achievable in future through integration of multiple data types.
Journal ArticleDOI
Classification of Paediatric Inflammatory Bowel Disease using Machine Learning
Enrico Mossotto,James J. Ashton,James J. Ashton,Tracy Coelho,Tracy Coelho,Robert Mark Beattie,Ben D. MacArthur,Sarah Ennis +7 more
TL;DR: While unsupervised modelling categorises patients into four subgroups, supervised approaches confirm the need of both endoscopic and histological evidence for an accurate diagnosis, providing a blueprint for ML use with clinical data.