Patient Scheduling in Clinical Studies with Multi-Agent Techniques.

Article · January 2006with4 Reads
Source: DBLP
    • "As an example, we mention the medical expert systems that must be capable to extend/adapt their knowledge-base by adding new knowledge or eliminating/changing the unnecessary or inaccurate knowledge. In the medical domain, there are proposed and used many medical computational systems that operate in isolation or cooperate with each other to solve medical problems (Huang et al, 1995; Fraser et al, 1998; Laita et al., 2001; Myritz et al., 2006; Iantovics, 2006; Iantovics, 2008; Iantovics, 2009). Medical expert systems represent relative classical applications used for medical diagnoses elaborations (Shortliffe, 1976; Kulikowski and Weiss, 1982; Aikins et al, 1983; Adlassing, 1986; Huang et al, 1995; Fraser et al, 1998; Laita et al., 2001; Bravata et al, 2004). "
    Full-text · Conference Paper · Oct 2010
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    • "But the dependency relationships among symptoms and the mapping relationships between symptom and syndrome are not considered in these methods, which are important to diagnosis in TCM. To lower the influences of irrelative symptoms, the mutual information between each symptom and disease is computed based on information entropy theory [10], which is utilized to assess the significance of symptoms.The paper [11] presents a multiagent system for supporting physicians in performing clinical studies in real time. The multiagent system is specialized in the controlling of patients with respect to their appointment behavior. "
    [Show abstract] [Hide abstract] ABSTRACT: The goal is to develop a novel approach for cardiac disease prediction and diagnosis using intelligent agents. Initially the symptoms are preprocessed using filter and wrapper based agents. The filter removes the missing or irrelevant symptoms. Wrapper is used to extract the data in the data set according to the threshold limits. The classification is based on the prior and posterior probability of the symptoms with the evidence value. Finally the symptoms are classified in to five classes namely absence, starting, mild, moderate, serious. Using the cooperative approach the cardiac problem is solved and verified.
    Full-text · Article · Jan 2010
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    • "In medical domains, there are proposed and used many medical systems that operate in isolation or cooperate with each other [3, 22, 8, 14, 15, 16, 17, 37, 38]. The paper [39] motivate that appropriate use of available information, knowledge and communication technologies can make a significant contribution towards achieving a sustainable health system and that the adoption of semantically interoperable health information systems. "
    [Show abstract] [Hide abstract] ABSTRACT: The development of efficient and flexible agent-based medical diagnosis systems represents a recent research direction. Medical multiagent systems may improve the efficiency of traditionally developed medical computational systems, like the medical expert systems. In our previous researches, a novel cooperative medical diagnosis multiagent system called CMDS (Contract Net Based Medical Diagnosis System) was proposed. CMDS system can solve flexibly a large variety of medical diagnosis problems. This paper analyses the increased intelligence of the CMDS system, which motivates its use for different medical problem’s solving.
    Preview · Article · Jan 2010
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