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Implementation of Software Agents and Advanced AoA for Disease Data Analysis.

K Vijayakumar1, K Pradeep Mohan Kumar2, Daniel Jesline3

  • 1Department of Computer Science &Engineering, St. Joseph's Institute of Technology, Chennai, India. mkvijay@msn.com.

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Summary

This study introduces an Intelligent Searching Approach (ISA) using artificial agents to analyze medical forums, providing more accurate solutions than manual methods. The system efficiently identifies and prioritizes the best diagnostic outcomes, saving time and ensuring solution perfection.

Keywords:
Disease data analysisIntelligent searching approachSoftware agents

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Area of Science:

  • Artificial Intelligence
  • Medical Informatics
  • Computational Linguistics

Background:

  • Traditional diagnostic approaches can yield contradictory solutions.
  • Manual analysis of extensive medical data is time-consuming and prone to errors.

Purpose of the Study:

  • To propose an Intelligent Searching Approach (ISA) that replaces traditional Agent oriented Approach (AoA).
  • To enhance diagnostic accuracy and efficiency by utilizing intelligent artificial agents.

Main Methods:

  • Employing intelligent artificial agents to dynamically analyze medical forums and blogs.
  • Utilizing Agent Communication Language (ACL) and FIPA for inter-agent communication.
  • Implementing a Global Agent to control local agents, consolidate solutions, and make final decisions.
  • Applying advanced clustering techniques for a prioritization matrix of suggested solutions.
  • Employing a recursive refining process to ensure optimal solution selection.

Main Results:

  • Achieved more accurate findings compared to manual approaches.
  • Minimized communication time between agents through centralized control by the Global Agent.
  • Generated a prioritized list of best solutions via clustering.
  • Successfully refined solutions recursively to ensure perfection.

Conclusions:

  • The Intelligent Searching Approach (ISA) offers a novel and efficient method for obtaining accurate diagnostic solutions.
  • This AI-driven approach significantly reduces time spent on data research and inter-agent communication.
  • The system ensures solution perfection without compromising efficiency.