Phenotyping of children with abdominal pain.

A. Scatter plots based on three new variables generated by unsupervised Uniform Manifold Approximation and Projection (UMAP). Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) found 3 distinct phenotypes. B. Hierarchical...

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Bibliographic Details
Main Author:	Kazuya Takahashi (69459) (author)
Other Authors:	Michalina Lubiatowska (22567103) (author), Huma Shehwana (6082751) (author), James K. Ruffle (20748127) (author), John A. Williams (420691) (author), Animesh Acharjee (3524051) (author), Shuji Terai (496086) (author), Georgios V. Gkoutos (8025890) (author), Humayoon Satti (22567106) (author), Qasim Aziz (4584709) (author)
Published:	2025
Subjects:	Medicine Cell Biology Developmental Biology Science Policy Infectious Diseases Biological Sciences not elsewhere classified three distinct phenotypes remain unclear due preliminary study aimed large birth cohort key predictive factors identifying targeted interventions guide future investigations general practitioner records explore associated factors develop predictive models based predictive model child &# 8217 developed using demographics observed ap rates identify ap phenotypes 67 ), showing prediction </ p 3 allergic diseases maternal comorbidities increased 50 &# 8211 40 &# 8211 predicting paediatric ap paediatric allergic diseases 3 maternal comorbidities xlink "> 1 allergic diseases xlink "> maternal demographics maternal comorbidities &# 8805 phenotype 3 paediatric ap allergic predisposition 676 ), 659 ), predicted probability phenotype 1 patient heterogeneity machine learning average age 340 ). 2 %) 1 years
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Phenotyping of children with abdominal pain.

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