Group decision making and Quality-of-Information in e-Health systems

Abstract

Abstract. Knowledge is central to the modern economy and society. Indeed, the knowledge society has transformed the concept of knowledge and is more and more aware of the need to overcome the lack of knowledge when has to make options or address its problems and dilemmas. One`s knowledge is less based on exact facts and more on hypotheses, perceptions or indications. Even when we use new computational artefacts and novel methodologies for problem solving, like the use of Group Decision Support Systems (GDSS), the question of incomplete information is in most of the situations marginalized. On the other hand, common sense tells us that when a decision is made it is impossible to have a perception of all the information involved and the nature of its intrinsic quality. Therefore, something has to be made in terms of the information available and the process of its evaluation. It is under this framework that a Multi-valued Extended Logic Programming language will be used for knowledge representation and reasoning, leading to a model that embodies the Quality-of-Information (QoI) and its quantification, along the several stages of the decision making process. In this way it is possible to provide a measure of the value of the QoI that supports the decision itself. This model will be here presented in the context of a GDSS for VirtualECare, a system aimed at sustaining online healthcare services.

Treating Colon Cancer Survivability Prediction as a Classification Problem

“…In this way, it will be possible for users to dynamically feed new cases to the prediction system and make it change in order to provide better survival predictions. This type of model could also prove to be very useful when integrated in computer-interpretable guideline systems, such as the one described in (Carneiro et al, 2008;Costa et al, 2011;Lima et al, 2011;Oliveira et al, 2013;Oliveira et al, 2014;Novais et al, 2016), as a way to provide dynamic knowledge to rule-based decision support. Future work also includes the development of conditional survivability models that allow the user to get a prediction knowing that the patient has already survived a number of years after diagnosis and treatment.…”

Developing an Individualized Survival Prediction Model for Rectal Cancer

“…Overall, the developed model was able to present a good performance with fewer features than the existing approaches. As future work we intend to construct a mobile application to make both models (colon and rectal cancer prediction models) available to the health care community and to integrate it in settings of ambient assisted living and group decision making [14,12]. In order to have the tool always updated and adapted to new patients, an on-line learning scheme is being prepared.…”

Marketing Information System (MkIS): Benefits for Small and Medium Enterprises in Fiji

“…Kerr et al (2007) suggest that the organizations need to enhance the quality of data for improving the decision making and thus, reducing the level of uncertainty for producing more timely and accurate decisions outcomes. According to Lima et al (2011) best decision related to health services can be made through the quality of information provided to the Health system (e-health system). One of the important supposition of decision making process and improvement of the quality process in business is the existence of the quality information (Zager and Zager, 2006).…”