Information Systems and Health Care IX: Accessing Tacit Knowledge and Linking It to the Peer-Reviewed Literature

Clinical decision-making can be improved if healthcare practitioners are able to leverage both the tacit and explicit modalities of healthcare knowledge, yet at present there do not exist knowledge management systems that support any active and direct mapping between these two knowledge modalities. In this paper, we present a healthcare knowledge-mapping framework that maps (a) the tacit knowledge captured in terms of email-based discussions between pediatric pain practitioners through a Pediatric Pain Mailing List (PPML), to (b) explicit knowledge represented in terms of peer-reviewed healthcare literature available at PubMed. We report our knowledge mapping strategy that involves methods to establish discussion threads, organize the discussion threads in terms of topic-specific taxonomy, formulate an optimal search query based on the content of a discussion thread, submit the search query to PubMed and finally to retrieve and present the search results to the user

Neural Networks and Child Language Development: Towards a `Conglomerate' Neural Network Simulation Architecture

Neural networks provide a basis for studying child language development in that such networks emphasise learning. We report a simulation of some key aspects of child language development during infancy. We argue that in order to simulate the uniquely human language learning, it is important to use a `conglomerate' neural network architecture that integrates the collective strengths of a variety of neural networks in some principled fashion to take into account the diverse nature of inputs to and outputs from a child learning language. We present such a `conglomerate' neural network architecture - ACCLAIM that integrates both supervised and unsupervised learning algorithms, to simulate the learning of concepts, words, conceptual and semantic relations and simple word-order rules, thus mimicking the production of child-like one-word and two-word language. The simulations carried out are `language informed' as realistic child language data has been used for training the neural network..

Data-Driven Healthcare Management: From a Philosophy to an Info-Structure

Business and scientific endeavours now routinely gather large quantities of data that can help in acquiring an intimate understanding of the parent enterprise, thus leading to value-added strategic and tactical decision support services. Today's healthcare enterprise, supported by Telemedicine based high-tech IT systems, also generate volumes of data---health related facts. It is our contention that data repositories, storing vital health data, need to be charged with harvesting data-driven decision support towards strategic planning and management of the healthcare enterprise---a vision shared by the MSC Telemedicine project. The proposal entails the extraction of tangible knowledge from raw health data by way of a suite of IT-driven Group Data Services (GDS). Here, we firstly present the philosophical foundation of a GDS environment that gleans knowledge from health data repositories, and secondly we specify a universal and generic GDS info-structure---the IT manifestation of the GD..