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Table 1 Patient characteristics

From: Performance and clinical utility of a new supervised machine-learning pipeline in detecting rare ciliopathy patients based on deep phenotyping from electronic health records and semantic similarity

 

Ciliopathy cases

Controls

# Training set

20

4844

# Test set

10

2387

# Total

30

7231

Sex ratio (M/F)

1.5

1

Age* (median (IQR))

14.8 (12–19.2)

11.5 (4.6–25.8)

% Syndromic forms

40%

NA

#HPO (median (IQR))

18 (10.3–35.8)

10 (6–18)

  1. *For each patient, age corresponds to the age at the date of the most recent EHR document. # Number of patients
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Orphanet Journal of Rare Diseases

ISSN: 1750-1172