Towards knowledge-infused automated disease diagnosis assistant

HIGHLIGHTS

• What: The authors investigate the following three research questions: (i) Are self-reports from patients sufficient for an accurate diagnosis? The authors propose a two-channeled knowledge-infused, discourse-aware disease identification (KI-DDI) model that leverages external medical knowledge encoded through a context-aware filtered knowledge graph for identifying diseases accurately and efficiently from patient-doctor communications.. In the subsequent paragraphs, the authors provide summaries of the pertinent works in these domains. The proposed model aims to identify the disease of the patient based on patient-doctor interaction.
• Who: Mohit Tomar from the Department . . .
  

   

  

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