Implementation of Software Agents and Advanced AoA for Disease Data Analysis.
To eliminate the possibilities of getting various contradicting solutions to a single problem during diagnosis, a single regular Agent oriented Approach (AoA) is replaced by Intelligent Artificial Agents that act like human and even dynamically decide in any situations known as Intelligent Searching...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 8 |
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| Autores principales: | , , |
| Formato: | computer program tables/charts Journal Article |
| Publicado: |
Springer Nature
Aug2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=137490067&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 137490067 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Aug2019 vid: 43 iid: 8 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 137490067 137490067 137490067 10.1007/s10916-019-1411-5 137490067 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Implementation of Software Agents and Advanced AoA for Disease Data Analysis. aug: au: Vijayakumar, K. Pradeep Mohan Kumar, K. Jesline, Daniel affil: Department of Computer Science &Engineering, St. Joseph's Institute of Technology, Chennai, India sug: subj: Data Analysis, Computer Assisted Artificial Intelligence Communication Decision Making, Computer Assisted Data Mining Computer Simulation Models, Theoretical Algorithms ab: To eliminate the possibilities of getting various contradicting solutions to a single problem during diagnosis, a single regular Agent oriented Approach (AoA) is replaced by Intelligent Artificial Agents that act like human and even dynamically decide in any situations known as Intelligent Searching Approach (ISA) is proposed. These agents are used to analyse the medical forums and results or findings are derived accurately than any manual approach. Multiple Agents have been used to analyse the blogs by dividing the work areas and communicating themselves using Agent Communication Language (ACL) and FIPA. The local solutions thus formed are forwarded to a global agent. This Global Agent controls all operations and makes the decision about the best solution. As the Global Agent controls all other agents, it eradicates unwanted and ineffective communication between the various local agents and hence keeping the time taken for communication at the minimum level. Based on these solutions a prioritization matrix is formed using advanced clustering techniques to create a prioritized content of suggested best solutions. Once the decision is made, the refining process runs several times recursively checking for all possible better solutions solving the input. On completion of this process, the Global Agent returns the exact result of the discussion. This process saves time rather than researching the entire blog for result data. This advanced approach lights a different way of obtaining solution keeping the time taken for discussion and intercommunication between the agents to the minimal level but not compromising on the perfection of the solution at the same time. pubtype: Academic Journal doctype: computer program tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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