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Erschienen in:
Corrected Overlap Weight and Clustering Coefficient Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

Association Rules and Network Analysis for Exploring Comorbidity Patterns in Health Systems

verfasst von : Giuseppe Giordano, Mario De Santis, Sergio Pagano, Giancarlo Ragozini, Maria Prosperina Vitale, Pierpaolo Cavallo

Erschienen in: Challenges in Social Network Research

Verlag: Springer International Publishing

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Abstract

The presence of patients affected by different diseases at the same time is becoming a major health and societal issue. In clinical literature, this phenomenon is known as comorbidity, and it can be studied from the administrative databases of general practitioners’ prescriptions based on diagnoses. In this contribution, we propose a two-step strategy for analyzing comorbidity patterns. In the first step, we investigate the prescription data with association rules extracted by a two-mode network (or bipartite graph) to find frequent itemsets that can be used to assist physicians in making diagnoses. In the second step, we derive a one-mode network of the diseases codes with association rules, and we perform the k-core partitioning algorithm to identify the most relevant and connected parts in the network corresponding to the most related pathologies.

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Vorheriges Kapitel Bootstrapping the Gini Index of the Network Degree: An Application for Italian Corporate Governance
Nächstes Kapitel A Mixture Model Approach for Clustering Bipartite Networks
Fußnoten
1
The interactome [26] is the whole set of molecular interactions in a given cell, or individual, and it is represented as a graph of the biological network. It includes all the interactions between molecules belonging to different biochemical families, such as nucleic acids, proteins, lipids, carbohydrates, hormones, etc. Interactomics [18] is a discipline at the intersection of bio-informatics and biology that deals with the study of networks of interactions and their consequences.
 
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Metadaten
Titel
Association Rules and Network Analysis for Exploring Comorbidity Patterns in Health Systems
verfasst von
Giuseppe Giordano
Mario De Santis
Sergio Pagano
Giancarlo Ragozini
Maria Prosperina Vitale
Pierpaolo Cavallo
Copyright-Jahr
2020
Buch
Challenges in Social Network Research

Print ISBN: 978-3-030-31462-0

Electronic ISBN: 978-3-030-31463-7

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-31463-7_5

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