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. 2022 Jul 14;12:12018. doi: 10.1038/s41598-022-15764-9

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© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Temporal Disease Network. (a) Example of the disease records for a single patient and its representation into disease paths. The Disease Network connects diseases that occur consecutively in patients' records. Edge weights w_ij, p-values, and $ϕ$ values are shown for raw data and represent the number of patients, the correlation coefficient, and the significance, respectively, for each progression step. (b) Nodes represent diagnoses (ICD9 at the 3-digit level) and links represent the number of patients with disease A before diseases B. For visualization purposes, the edge directions were merged as single undirected edges, edges with $ϕ$ < 0.001 were filtered, and disconnected nodes resulting from this filtering were omitted. The full network contains 718 nodes and 60,425 edges, while the visualization shows 638 nodes and 4,582 edges. The labels highlight diseases mentioned throughout the text and their corresponding nodes in the network.