Summary
The Internet has become an important source of information for physicians seeking immediate data for the management of patients and for those developing decision-making methodologies and guidelines for clinical practice. In this study, components and subsystems of a medical decision support system are presented. An artificial neural network model, which is one of the subsystems of the differential diagnosis component, has been proposed as a reasoning tool to support medical diagnosis. The input data of artificial neural network models used in different medical diagnosis can be obtained via the Internet. The present study is concerned with the application of artificial neural network model to diabetes prediction. Demographic and medical data of diabetics and non-diabetics obtained via the Internet were used as the artificial neural network inputs. The accuracy of the neural network's results has shown that the diabetes prediction is feasible by the neural network described in this study.
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Extract
Use of the Internet in Medical Decision-Making: A Model Developed for Diabetes Prediction
1. Introduction
In the last decade, information and communication technologies have seen enormous growth and have been introduced in various degrees to the medical environment. The extra processing power and facilities open up the scope for much more powerful processing and networking of medical applications. Communication networks are becoming increasingly large in size and heterogeneous in nature. Recent advantages in communication technologies have contributed to an explosion of new services directed at the medical environment. Fig. 1 gives mapping between medical applications and network evolution [1]. The general goal of using communication technologies in medical environments is to improve the overall quality of health care at an affordable cost. This requires close interaction between health care pr...See the full content of this document
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