Age density patterns in patients medical conditions: A clustering approach

This paper presents a data analysis framework to uncover relationships between health conditions, age and sex for a large population of patients. We study a massive heterogeneous sample of 1.7 million patients in Brazil, containing 47 million of health records with detailed medical conditions for vi...

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Bibliographic Details
Published in:PLoS computational biology 2018-06, Vol.14 (6), p.e1006115-e1006115
Main Authors: Alhasoun, Fahad, Aleissa, Faisal, Alhazzani, May, Moyano, Luis G, Pinhanez, Claudio, González, Marta C
Format: Article
Language:English
Subjects:
Age
Age (Biology)
BASIC BIOLOGICAL SCIENCES
Biochemistry & Molecular Biology
Bioinformatics
Biology and Life Sciences
Cancer
Chronic obstructive pulmonary disease
Clustering
Codes
Comorbidity
Data analysis
Data processing
Demographic aspects
Disease control
Disease prevention
Electronic health records
Health aspects
Health care
Mathematical & Computational Biology
Medical records
Medicine and Health Sciences
Patients
People and places
Population
Population studies
Public health
Sex differences (Biology)
Software
Studies
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Summary:This paper presents a data analysis framework to uncover relationships between health conditions, age and sex for a large population of patients. We study a massive heterogeneous sample of 1.7 million patients in Brazil, containing 47 million of health records with detailed medical conditions for visits to medical facilities for a period of 17 months. The findings suggest that medical conditions can be grouped into clusters that share very distinctive densities in the ages of the patients. For each cluster, we further present the ICD-10 chapters within it. Finally, we relate the findings to comorbidity networks, uncovering the relation of the discovered clusters of age densities to comorbidity networks literature.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1006115