ADDS: An automated disease diagnosis-aided system

Abstract

This demo paper describes an automated disease diagnosis-aided system in healthcare (ADDS). The system contains four main components: medical knowledge base, data processing, data analytics, and interactive crowdbased feedback. First, we build a semantic-rich knowledge base using practical clinical data that are collected from several collaborated hospitals. Different from existing knowledge bases, we focus on building the personalized knowledge graph for each patient. Second, we develop an automated integration platform for patients to upload and manage their health data. The data are integrated into their clinical data, and then used as input for the data analytics tool. The automated diagnosis results are retuned and visualized to the corresponding patients and doctors. If the doctors have questions about the results, they can use our provided interactive feedback system to contact the patients. The feedbacks from expert doctors are used to improve the accuracy of the data analytics tool.