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Inference on chains of disease progression based on disease networks.

Dong-Gi LeeMyungjun KimHyunjung Shin
Published in: PloS one (2019)
A disease network consisting of 3,302 diseases was constructed based on four sources of biomedical data: disease-protein relations, biological pathways, clinical history, and biomedical literature information. The last three sets of data contain prior-posterior information, and they endow directionality on the edges of the network. The results were interesting and informative: for example, when colitis and respiratory insufficiency were set as a source disease and a target one, respectively, five progression chains were found within several seconds (when k = 5). Each chain was provided with a progression score, which indicates the strength of plausibility relative to others. Similarly, the proposed method can be expanded to any pair of source-target diseases in the network. This can be utilized as a preliminary tool for inferring complications or progressions between diseases.
Keyphrases
  • electronic health record
  • systematic review
  • healthcare
  • wastewater treatment
  • small molecule
  • drinking water
  • artificial intelligence