Phenotyping of children with abdominal pain.

Phenotyping of children with abdominal pain.

<p><b>A.</b> 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>B.</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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