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Updated: Dec 27, 2025

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DISNET: a framework for extracting phenotypic disease information from public sources.

Gerardo Lagunes-García1, Alejandro Rodríguez-González1,2, Lucía Prieto-Santamaría1

  • 1Centro de Tecnología Biomédica, Universidad Politécnica de Madrid, Pozuelo de Alarcón, Madrid, Spain.

Peerj
|February 29, 2020
PubMed
Summary

DISNET is a web system that extracts disease and symptom knowledge from public sources like Wikipedia and PubMed. It creates a disease network dataset, aiding medical knowledge integration and analysis.

Keywords:
Disease understandingDisnet frameworkNatural language processingPhenotypic informationPublic sources

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Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Medical Knowledge Discovery

Background:

  • Integrating fragmented medical knowledge from diverse sources is a global health challenge.
  • A comprehensive disease and symptom dataset can enhance and interconnect existing medical data.
  • Publicly available information offers a valuable resource for expanding medical knowledge.

Purpose of the Study:

  • To present DISNET, a web-based system for extracting and organizing medical knowledge.
  • To enable the creation of customizable disease networks from signs and symptoms.
  • To facilitate the analysis and interrelation of diseases.

Main Methods:

  • Information on diseases and phenotypic manifestations is extracted from Wikipedia and PubMed.
  • Text mining and natural language processing techniques are employed for data extraction.
  • The DISNET system periodically updates its knowledge base.

Main Results:

  • The system was validated on Wikipedia and PubMed texts with relevant accuracy.
  • A comprehensive symptoms-disease dataset is generated and accessible via an API.
  • User interaction and information extraction for subsequent analyses are demonstrated.

Conclusions:

  • DISNET retrieves knowledge on disease signs, symptoms, and diagnostic tests across all categories.
  • The system allows tracking the evolution of medical terms over time.
  • Validation suggests DISNET is suitable for extracting disease and diagnostic terms, with room for improvement.