Agent-based intelligent medical diagnosis system for patients

Yingfeng Zhang, Sichao Liu, Zhenfei Zhu, Shubin Si

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

BACKGROUND: According to the analysis of the challenges faced by the current public health circumstances such as the sharp increase in elderly patients, limited medical personnel, resources and technology, the agent-based intelligent medical diagnosis system for patients (AIMDS) is proposed in this research. OBJECTIVE: Based on advanced sensing technology and professional medical knowledge, the AIMDS can output the appropriate medical prescriptions and food prohibition when the physical signs and symptoms of the patient are inputted. METHODS: Three core modules are designed include sensing module, intuition-based fuzzy set theory/medical diagnosis module, and medical knowledge module. RESULTS: The result shows that the optimized prescription can reach the desired level, with great curative effect for patient disease, through a case study simulation. CONCLUSION: The presented AIMDS can integrate sensor technique and intelligent medical diagnosis methods to make an accurate diagnosis, resulting in three-type of optimized descriptions for patient selection.

Original languageEnglish
Pages (from-to)S397-S410
JournalTechnology and Health Care
Volume23
DOIs
StatePublished - 17 Jun 2015

Keywords

  • agent
  • intelligent medical diagnosis
  • Intuitionistic fuzzy set theory
  • medical knowledge
  • sensing technology

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