Patient Information Maintaining & Analyzing

Hospitals presently use a manual system for the management and maintenance of essential info. This system needs various paper forms, with knowledge stores unfold throughout the hospital management infrastructure. Usually, info (on forms) is incomplete or does not follow management standards. Forms are usually lost in transit between departments requiring a comprehensive auditing method to confirm that no important info is lost. Multiple copies of similar info exist within the hospital and should result in inconsistencies in knowledge in numerous knowledge stores. A significant part of the operation of any hospital involves the acquisition, management, and timely retrieval of nice volumes of knowledge. This info generally involves; patient personal info and case history, staff information and ward scheduling, scheduling programming, operating theatre scheduling, and numerous facilities waiting lists. All of this info should be managed in an economical and cost-wise fashion so that an institution's resources could also be effectively utilized. Patient info maintaining & Analyzing can automate the management of the hospital creating additional economic and the error free. It aims at standardizing data, consolidating data, reducing inconsistencies, and ensuring data integrity.

Word from the editors

Graph structures naturally model connections. In natural language processing (NLP) connections are ubiquitous, on anything between small and web scale. We find them between words – as grammatical, collocation or semantic relations – contributing to the overall meaning, and maintaining the cohesive structure of the text and the discourse unity. We find them between concepts in ontologies or other knowledge repositories – since the early ages of artificial intelligence, associative or semantic networks have been proposed and used as knowledge stores, because they naturally capture the language units and relations between them, and allow for a variety of inference and reasoning processes, simulating some of the functionalities of the human mind. We find them between complete texts or web pages, and between entities in a social network, where they model relations at the web scale. Beyond the more often encountered ‘regular’ graphs, hypergraphs have also appeared in our field to model relations between more than two units.

User-Centered Design of Online Learning Communities

This chapter aims to introduce User-Centred Design and its basic concepts associated with online learning communities. Another aim is to search for guidelines to ensure Quality in online learning. Human Computer Interaction for Education provides the missing holistic approach for online learning. Functioning in a socio-technical framework, online learning communities combine information and knowledge stores situated in shared social spaces using social learning software. In recent years, educational technologists linked the theory and systems design in education. However, several disciplines combine in online learning. User-Centred Design provides the cross-disciplinary approach that appears to be essential for Quality in online learning. Thus, seven guidelines for experts’ evaluation are proposed as signposts: intention, information, interactivity, real time evaluation, visibility, control and support.

User-Centered Design Principles for Online Learning Communities

This chapter aims to introduce user-centered design and its basic concepts associated with online learning communities. Another aim is to search for guidelines to ensure quality in online learning. Human computer interaction for education provides the missing holistic approach for online learning. Functioning in a sociotechnical framework, online learning communities combine information and knowledge stores situated in shared social spaces using social learning software. In recent years, educational technologists linked theory and systems design in education. However, several disciplines combine in online learning. User-centered design provides the cross-disciplinary approach that appears to be essential for quality in online learning design and engineering. Thus, seven guidelines for experts’ evaluation are proposed as signposts: intention, information, interactivity, real-time evaluation, visibility, control, and support.