Frontiers in Health Informatics
Volume:3 Issue: 4, 2014

In this paper conceptual and logical model of Mobile Health services risk management by the use of context aware systems is provided. Mobile health (M-Health) refers to using portable electronic devices having application for delivering health services and patient’s information management. M-Health can offer various services remotely in prevention, detection, control, and treatment of disease or in the conditions of disaster for a patient or an environment. These services can have more acceptable quality by the help of Context Aware Systems which are defined as the capacity of computing equipment for detection, feeling, interpreting, and replying to user’s local environmental aspects and computing equipment itself. In this paper, executive model is offered for managing services of M-Health based on context aware systems. One of the supplies of developing a context aware system is having a clear and well-defined definition of context and developing appropriate context information provider. In order to deliver high quality and well- managed M-Health services, in the form of context aware systems, having clinical risk management plan is necessary. M-Health services need to develop appropriate communication strategies for interacting with stockholders at each stage of clinical risk management process. Using clinical risk management in M-Health makes it possible, by the help of context aware systems, that those risks which are primarily at three sides of services provider, communicating channels and services receiver, well identified and managed, thereby they can offer qualified and precise services.

Telemedicine is the use of modern telecommunications and information technologies to provide clinical care to individuals located at a distance, and to support the transmission of information needed to provide that care. According to this definition, the main tool for establishing direct telemedicine between patient and physician is different kinds of communication networks which considering their features and challenges seem to be necessary to establish a efficient communication. The goal of this paper is to study challenges, features and weaknesses of each communication network that has the ability to be used in telemedicine, so appropriate solution can be chosen for different telemedicine conditions. Various telemedicine needs, either in terms of different kinds of telemedicine or in terms of wireless application domains of suitable wireless networks for telemedicine and also general challenges of wireless networks for using in telemedicine are the topics which are studied in this paper to provide appropriate telemedicine solution.

Because of the high dimension of data in a variety of bioinformatics science, and inevitably reduce of these dimension, in recent decades, the use of feature selection techniques in bioinformatics has become a basic need to build models. In this article a hybrid method based on the binary particle swarm optimization algorithm and SVM classification algorithm are provided to select features. Classifieds efficiency and the number of optional features are used as the heuristic information for the proposed method. So to choose the features you don’t need to know previous information about the property. Efficiency of Proposed method has been tested on a data set of bioinformatics. Also to compare the effectiveness are used two measures of accuracy and vector size of the selected feature. Implementation results show the high efficiency of the proposed method on the used data set.