Socially interactive CDSS for u-life care

Abstract

Clinical decision support system (CDSS) is an interactive decision support system computer software, which is designed to assist physicians and other health professionals with decision making tasks, such as determining diagnosis of patient data, disease prevention, and alerting adverse drug events. It links health observations with health knowledge to influence health choices by clinicians for improved health care. Different from conventional CDSSs which focus on diagnosis assistance, the focus of our CDSS is to provide recommendations and healthcare services for chronic disease patients by long term monitoring. To make our CDSS more intelligent, it induces the patients to interact with the system. By continuously learning and digesting patients' experience and knowledge, the knowledge base of our CDSS is self-evolutionary and dynamically enhanced. We mainly develop two modules to achieve the function of social interaction. Firstly, Knowledge Authority Module (KAM) is developed which is capable of manipulating and preprocessing social data. Secondly, to support self-evolutionary and dynamical learning, we designed the rough set based inference engine. Through social interaction, the patients can get continuous relevant medical recommendations from the system, so they can get a chance to improve their health conditions which in turns keeping on their quality of life.

Context Representation and Fusion: Advancements and Opportunities

“…These systems are based on the general user phenomenon of acting and reacting in a given context, which gives a user the capability of adapting with the situation. However, the physical and cyber world offers a richer environment for context acquisition and handling [17,25] that not only help in replicating user action and reaction for an event but also consider user intention, sentiments and preferences for user behavior in a given situation.…”

“…Creating a system that is open to new sensors at runtime will further complicate the process; however, it is the real essence of context-aware system to adapt with the changing environment [2]. In addition to a user’s physical world, where users perform different activities and the environment in which the user is; the cyber world where users interact in social media [25] and share their sentiments about different entities [26] is also an important context to be considered for understanding users’ intention, which eventually will help the system to understand the overall context of the user [2,15]. Moreover, in any domain there are rules and regulations that are followed, which are usually encoded as domain knowledge.…”

“…In [25] the system has processed the social interaction of patients. Based on their social media interactions and activities, the system generates intelligent recommendations.…”

Towards A Self Adaptive System for Social Wellness

“…, healthcare. The complex data also introduce uncertainty, specifically relating to the problems in healthcare services [ 6 , 7 ]. Nowadays, people are more interested in better healthcare, which results in high cost healthcare services.…”

DDSS: Dynamic decision support system for elderly

“…In [10], realtime activities are recognized using diverse sensors are used for situation analysis. Research in [5] focused on the social interaction of patients. Based on the experiences shared, it generates intelligent service recommendations and eliminates their isolation.…”