Artificial Intelligence Applied to the Modeling and Implementation of a Virtual Medical Office
This chapter aims at presenting an overview of two Artificial Intelligence (AI) techniques: Case-Based Reasoning (CBR) and Genetic Algorithm (GA). It will present two implementation models, one for each technique, proposed by the Technology and Science Ce
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Technology and Science Center, Catholic University of Bras´ılia (UCB), Bras´ılia, Brazil Medicine Department, University of Bras´ılia (UnB), Bras´ılia, Brazil
This chapter aims at presenting an overview of two Artificial Intelligence (AI) techniques: Case-Based Reasoning (CBR) and Genetic Algorithm (GA). It will present two implementation models, one for each technique, proposed by the Technology and Science Center (CCT) of the Catholic University of Bras´ılia (UCB), in Brazil. Afterwards, a case study will show the results of the implementation of those models in the context of IACVIRTUAL, which is a project of a Webbased Virtual Medical Office that has been developed by the researchers of CCT. Therefore, the chapter will provide a practical demonstration of the application of CBR and GA in the field of Health, specifically as to the support to diagnosis.
1 Medical Diagnosis and Knowledge Transfer The medical profession is very influenced by the scientific advances of the related areas. Like in most of the current professions, medical professionals must be always up-to-date about the latest technologies. Nowadays, knowledge generation and knowledge transfer are key elements for success and a professional challenge as well [1]. According to Davenport and Prusak [2], human beings learn better from histories. The research of Schank [3] and the work of his student Kolodner [4] show that knowledge transfer gets more efficacious when it occurs by means of a convincing, elegant, eloquent narrative. The use of narratives is one of the best ways to learn and to teach complex subjects. Most of the times, it is possible to structure histories to transmit knowledge without substantial loss of the power of communication. Throughout the diagnosis process, the medical professionals perform several inferences from the body malfunctions. Those inferences derive from S.M.C. de Almeida et al.: Artificial Intelligence Applied to the Modeling and Implementation of a Virtual Medical Office, Studies in Computational Intelligence (SCI) 116, 169–190 (2008) c Springer-Verlag Berlin Heidelberg 2008 www.springerlink.com
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observation (the patient’s clinical history, signals, symptoms, routine tests, response to manipulation, time elapsed since some events); the clinical, physiological, biochemical, anatomical, pathological knowledge of the doctor; the experience of diagnosing similar cases; and the common sense and intuition [5]. The medical professionals use their past experiences widely in the process of gathering and interpreting information. Those past experiences are essential because they reduce the number of unnecessary questions, avoid superfluous test requisitions, and make the information management more efficient [5]. As can be seen, the medical diagnosis is a very complex process. It demands intuition, reasoning, experience and the analysis of information from distinct sources. Medical experts use several computational techniques to support the decision in the medical diagnosis [6]. Among the computational tech
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