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PubMed1992

Instructional multimedia computing in the health sciences.

This article focuses on the development and utilization of interactive videodisc (IVD) and multimedia instruction in the health sciences. The characteristics of IVD and multimedia are outlined and the four levels of IVD systems that can be used in health science education are described. The advantages of utilization of videodisc or multimedia materials are presented, as well as instructional approaches. Potential applications such as simulations, tutorials, role-modeling, and drill-and-practice are described. Research findings, levels of curricular integration, instructional delivery, and courseware networking are also described. The article concludes with suggestions for institutional development of IVD materials or the incorporation of off-the-shelf programs into health science curricula.

Computer-Assisted Instruction↗
PubMed2006

How do forensic scientists learn to become competent in casework reporting in practice: a theoretical and empirical approach.

In their day-to-day work, carrying out complex tasks, forensic scientists use a combination of explicit, codified standard operating procedures and tacit knowledge developed through their ongoing practice. We show that tacit knowledge is an integral part of the activities of expert forensic science practitioners who continually add to their knowledge repertoire by engaging other scientists through communities of practice. We wish to shed fresh light on the gaining of tacit knowledge by forensic scientists during their apprentice formative years, termed as legitimate peripheral participation. In quantifying tacit knowledge exchanges, we use social network analysis, a methodology for the analysis of social structures, to map relational knowledge flows between forensic scientists within communities of practice at the Forensic Science Laboratory, Ireland. This paper sheds light on the importance of tacit knowledge within the training regime of forensic scientists and its recognition as equal to the part played by explicit knowledge.

Forensic Sciences↗
PubMed1996

The changing face of health information and health information work: a conceptual framework.

The purpose of this paper is to examine the changes in health information and health information work using a conceptual framework and to consider the implication of these changes for health sciences librarians. The notion of what constitutes information depends heavily on the perspective of those defining the term. In the health care domain, numerous established concepts of information exist, many clustering around disciplines and professions. Various information professions-for example, health sciences librarians, information-systems managers, and medical-records administrators--have differing core concepts of information. Although these established concepts of information may seem immutable, they are cultural facts and can and do change. Global networking and changes in health care delivery are just two of many environmental forces that are changing the way the health domain views health information and the way it values the patterns and practices traditionally associated with established types of information and information professions. As new concepts of information arise, the possibility for new expert work surrounding information also arises. Andrew Abbott's systems theory of professions, adapted to the health domain, suggests that some forms of established expert information work may diminish while new types may arise and that both established and new information professions will struggle with each other for official sanction, or jurisdiction, to perform new expert work. This competitive struggle is likely to produce a new balance of information work and roles among the information professions. The specialty areas of library and information science, the heartland of our knowledge base, are as relevant in the electronic environment as in the print environment. Our profession's challenge now is to redefine and communicate our jurisdictional place in the emerging health information environment.

Computer Communication Networks↗
PubMed1997

United States vaccine research: a delicate fabric of public and private collaboration. National Vaccine Advisory Committee.

In the last 20 years, two thirds of all new vaccines provided worldwide have been produced by a US network of independent industrial, governmental, and academic partners engaged in vaccine research and development. Vaccines are complex products and the science of vaccinology is difficult. To achieve the full promise of modern science and technology to prevent and treat disease by immunization, the delicate fabric of America's cooperative and collaborative vaccine research relationships must be sustained and strengthened. The major partners are the federal government; four large companies--two US-headquartered (Wyeth-Lederle Biologics and Vaccines and Merck & Co), two foreign firms (SmithKline Beecham and Pasteur Mérieux Connaught); and academia. Of the $1.4 billion that fund US vaccine research and development annually, 46% comes from vaccine sales, 36% from taxpayers, and 18% from risk capital. Vaccine innovation could be strengthened by improved public and policy maker understanding of the vaccine development network; declarations of partnership; interactive dialog with federal advisory bodies; public forums for government and industry to listen to patients, providers and researchers; sabbatical assignments between partners; mechanisms to share industries' market research with public immunization programs; continued active industry participation in the Advisory committee on Immunization Practices and the National Vaccine Advisory committee; increased collaboration between industry and the National Institutes of Health for clinical research; harmonization of the Advisory Committee on Immunization Practices vaccine recommendations and the Food and Drug Administration package inserts; and public policies to foster the partnership's collaboration and robustness. The optimal size and configuration of the US vaccine enterprise should be debated only in the context of a full understanding of how the current system works and its record of effectiveness. These National Vaccine Advisory Committee recommendations are directed at developing public policies to foster and sustain vaccine innovation and ensure the timely introduction and supply of new vaccines needed by this nation and the world.

Cooperative Behavior↗
PubMed2001

Ngi and Internet2: accelerating the creation of tomorrow's internet.

Internet2 is a consortium of leading U.S. universities working in partnership with industry and the U.S. government's Next Generation Internet (NGI) initiative to develop a faster, more reliable Internet for research and education including enhanced, high-performance networking services and the advanced applications that are enabled by those services [1]. By facilitating and coordinating the development, deployment, operation, and technology transfer of advanced, network-based applications and network services, Internet2 and NGI are working together to fundamentally change the way scientists, engineers, clinicians, and others work together. [http://www.internet2.edu] The NGI Program has three tracks: research, network testbeds, and applications. The aim of the research track is to promote experimentation with the next generation of network technologies. The network testbed track aims to develop next generation network testbeds to connect universities and federal research institutions at speeds that are sufficient to demonstrate new technologies and support future research. The aim of the applications track is to demonstrate new applications, enabled by the NGI networks, to meet important national goals and missions [2]. [http://www.ngi.gov/] The Internet2/NGI backbone networks, Abilene and vBNS (very high performance Backbone Network Service), provide the basis of collaboration and development for a new breed of advanced medical applications. Academic medical centers leverage the resources available throughout the Internet2 high-performance networking community for high-capacity broadband and selectable quality of service to make effective use of national repositories. The Internet2 Health Sciences Initiative enables a new generation of emerging medical applications whose architecture and development have been restricted by or are beyond the constraints of traditional Internet environments. These initiatives facilitate a variety of activities to foster the development and deployment of emerging applications that meet the requirements of clinical practice, medical and related biological research, education, and medical awareness throughout the public sector. Medical applications that work with high performance networks and supercomputing capabilities offer exciting new solutions for the medical industry. Internet2 and NGI,strive to combine the expertise of their constituents to establish a distributed knowledge system for achieving innovation in research, teaching, learning, and clinical care.

Internet↗
PubMed1999

Awareness of the earth and possibilities for new science education in the Internet age.

The internet as "the nervous system of global size" and multimedia technology have changed our global experience radically and suggests possibilities of entirely new approaches to the conventional education of sciences and the environment. They are not merely the changes where printed text books are converted into dynamic things with vivid appeal to our senses and information about the world's museums and art galleries, digitalized and shared by all. If the seismic activities occurring every day in various parts of the world can be seen in real form directly through the internet by all the people of the world, how will children's views of the earth change and how will their scientific understanding improved? If there was a system whereby one could monitor, in real time, how one member or others of the world net surf the global home pages, and if one could follow the "moving" process on the internet, children would certainly appreciate the presence of the internet as a global network of information. The web site "Sensorium" (http://www.sensorium.org) was created by us in an effort to put these live experiences of the internet into design. Sensorium is not a site merely to digitalize and list the existing knowledge and data. It is an experiment for the Digital Museum as a new "forum" where we may experience and share a moment. It is also an attempt to create tools for science and environment education which are only available on the network.

Child↗
PubMed1991

Population behavior change: a theory-based approach.

Behavioral science provides useful ideas about how programs of mass communication and community participation can produce synergistic influences on the lifestyles and policy decisions of populations and their representatives. Media campaigns featuring real-life behavior models and community networks mobilized to promote behavior change provide a theoretically sound paradigm for community-level activities to accelerate the diffusion of innovation in health. Illustrative case studies demonstrate how behavioral science concepts can be applied to preventing HIV infections and to promoting citizen lobbying against selected nuclear weapons systems.

Health Behavior↗
PubMed2000

Basic concepts of artificial neural network (ANN) modeling and its application in pharmaceutical research.

Artificial neural networks (ANNs) are biologically inspired computer programs designed to simulate the way in which the human brain processes information. ANNs gather their knowledge by detecting the patterns and relationships in data and learn (or are trained) through experience, not from programming. An ANN is formed from hundreds of single units, artificial neurons or processing elements (PE), connected with coefficients (weights), which constitute the neural structure and are organised in layers. The power of neural computations comes from connecting neurons in a network. Each PE has weighted inputs, transfer function and one output. The behavior of a neural network is determined by the transfer functions of its neurons, by the learning rule, and by the architecture itself. The weights are the adjustable parameters and, in that sense, a neural network is a parameterized system. The weighed sum of the inputs constitutes the activation of the neuron. The activation signal is passed through transfer function to produce a single output of the neuron. Transfer function introduces non-linearity to the network. During training, the inter-unit connections are optimized until the error in predictions is minimized and the network reaches the specified level of accuracy. Once the network is trained and tested it can be given new input information to predict the output. Many types of neural networks have been designed already and new ones are invented every week but all can be described by the transfer functions of their neurons, by the learning rule, and by the connection formula. ANN represents a promising modeling technique, especially for data sets having non-linear relationships which are frequently encountered in pharmaceutical processes. In terms of model specification, artificial neural networks require no knowledge of the data source but, since they often contain many weights that must be estimated, they require large training sets. In addition, ANNs can combine and incorporate both literature-based and experimental data to solve problems. The various applications of ANNs can be summarised into classification or pattern recognition, prediction and modeling. Supervised 'associating networks can be applied in pharmaceutical fields as an alternative to conventional response surface methodology. Unsupervised feature-extracting networks represent an alternative to principal component analysis. Non-adaptive unsupervised networks are able to reconstruct their patterns when presented with noisy samples and can be used for image recognition. The potential applications of ANN methodology in the pharmaceutical sciences range from interpretation of analytical data, drug and dosage form design through biopharmacy to clinical pharmacy.

Algorithms↗
PubMed1999

Assessing and enhancing medical students' computer skills: a two-year experience.

In 1984, the Association of American Medical Colleges (AAMC) issued recommendations for the reform of medical education. One recommendation was that information sciences be incorporated into the medical curriculum. In fall 1996, a survey was conducted to learn more about computer use by medical students at the Rockford regional site of the University of Illinois at Chicago College of Medicine. The purpose of the survey was to gather information not only about computer skills, but also about overall comfort level in using computers and about expectations for enhancing computer skills while attending medical school. Over a two year period, 208 students representing four classes received this survey in their e-mail. Non-respondents received a follow-up print copy in their student mailboxes. Results, based on a 60% response rate, showed a majority of Rockford students entered medical school with good skills in using e-mail and word processing, but many lacked the skills necessary to search the medical literature or to use computer-assisted instructional programs. Overall, 80% of students expected to learn more about computers while attending medical school. Results contributed to an increased effort to integrate computer applications into the medical curriculum and to use computers as a means of communicating with students.

Computer Communication Networks↗
PubMed2004

Artificial neural network technologies to identify biomarkers for therapeutic intervention.

High-throughput technologies such as DNA/RNA microarrays, mass spectrometry and protein chips are creating unprecedented opportunities to accelerate towards the understanding of living systems and the identification of target genes and pathways for drug development and therapeutic intervention. However, the increasing volumes of data generated by molecular profiling experiments pose formidable challenges to investigate an overwhelming mass of information and turn it into predictive, deployable markers. Advanced biostatistics and machine learning methods from computer science have been applied to analyze and correlate numerical values of profiling intensities to physiological states. This article reviews the application of artificial neural networks, an information-processing tool, to the identification of sets of diagnostic/prognostic biomarkers from high-throughput profiling data.

Animals↗
PubMed2006

Thermodynamics of ions and water transport in porous media.

The thermodynamic framework of Prigogine, de Groot, and Mazur is extended to study the transport of ions and water in thermoporoelastic materials assuming infinitesimal deformations. New expressions are developed for the first and second principles of nonequilibrium thermodynamics of multicomponent systems and a generalized power balance equation is derived. For porous materials, all the components cannot be treated on a symmetric basis. A Lagrangian framework associated with deformation of the solid phase is introduced and, in this framework, Curie's principle is used to set up the form of the linear constitutive equations describing the transport of ions, water, and heat through the pore network. The material properties entering these equations were recently obtained by Revil and Linde [J. Colloid Interface Science 302 (2006) 682-694] using a volume-averaging approach based in the Nernst-Planck and Stokes equations. This provides a way to relate the material properties entering the constitutive equations to two textural parameters characterizing the topology of the pore space of the material (namely the tortuosity of the pore space and the permeability). The generalized power balance equation is used to derive the linear poroelastic constitutive equations (including the osmotic pressure) to describe the reversible contribution of deformation of the medium in response to ions and water transport through the connected porosity.

Elasticity↗
PubMed1997

Informational Capacity and Recall Quality in Sparsely Encoded Hopfield-like Neural Network: Analytical Approaches and Computer Simulation.

A sparsely encoded Hopfield-like attractor neural network is investigated analytically and by computer simulation. Informational capacity and recall quality are evaluated. Three analytical approaches are used: replica method (RM); method of statistical neurodynamics (SN); and single-step approximation (SS). Computer simulation confirmed the good accuracy of RM and SN for all levels of network activity. SS is accurate only for large sparseness. It is shown that informational capacity monotonically increases when sparseness increases, while recall quality changes nonmonotonically: initially it decreases and then increases. Computer simulation revealed the main features of network behaviour near the saturation which are not predicted by the used analytical approaches. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMed1997

An Incremental Adaptive Network for On-line Supervised Learning and Probability Estimation.

In this paper, a novel hybrid utilization of the Fuzzy ARTMAP (FAM) neural network and the Probabilistic Neural Network (PNN) is proposed for on-line learning and probability estimation tasks. There are two distinct advantages to the hybrid network. First, FAM is used as an underlying clustering algorithm to classify the input patterns into different recognition categories during the learning phase, resulting in a significant reduction in the number of pattern nodes required in the PNN. Second, a non-parametric posterior probability distribution estimation procedure, in accordance with the PNN paradigm (i.e. the Parzen-windows estimator), is employed during the prediction phase, where a probabilistic interpretation corresponding to Bayes decision theory can be provided for the predictions of FAM. In addition, several modifications are proposed to integrate both of the networks effectively into a unified platform for enhancing generalization. This hybrid approach also realizes an incremental learning system in which the necessity to specify a static network configuration a priori is eliminated as the network is able to "grow" to accommodate new input patterns sequentially and can thus operate in non-stationary environments. The performance of the network is evaluated with benchmark classification tasks and the results are compared with other approaches. Simulation results indicate that this hybrid network is capable of achieving a value near to the Bayes optimal classification rate. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMedDate not supplied

Cognitive evaluation of decision making processes and assessment of information technology in medicine.

This paper describes cognitive methods for analyzing medical decision making and evaluating medical information systems. The overall approach focuses on understanding the processes involved in the decision making and reasoning of health care workers, both with and without the use of information technologies. The issue of developing appropriate evaluation tools, for use in the design and analysis of medical information systems is considered to be of great importance. However, conventional methods are limited in their ability to identify and characterize the effects of information technology on the cognitive processes involved in decision making and reasoning. In this paper a range of methods are described involving video recording for collecting data on the use of information systems. The techniques described allow for the collection of an integrated data set consisting of transcripts of health care workers as they 'think aloud' in interacting with a medical system, along with complete video records of user-computer interaction. In addition, the methods can be extended to allow for the collection of process data from video recording of systems in actual clinical and emergency situations. The use of a variety of approaches, borrowing from research in cognitive science, is discussed. The development and application of these evaluation methods within the Canadian Centres of Excellence network HEALNet is subsequently described. Finally, implications for the development and evaluation of medical information systems are considered.

Cognition↗
PubMed2004

Brazilian LTER: ecosystem and biodiversity information in support of decision-making.

Brazil officially joined the International Long Term Ecological Research (ILTER) network in January 2000, when nine research sites were created and funded by the Brazilian Council for Science and Technology (CNPq). Two-years later some positive signs already emerge of the scientific, social and political achievements of the Brazilian LTER program. We discuss examples of how ecosystem and biodiversity information gathered within a long-term research approach are currently subsidizing decision-making as regards biodiversity conservation and watershed management at local and regional scales. Success in this respect has often been related to satisfactory communication between scientists, private companies, government and local citizens. Environmental education programs in the LTER sites are playing an important role in social and political integration. Most examples of integration of ecological research to decision-making in Brazil derive from case studies at local or regional scale. Despite the predominance of a bottom-up integrative pathway (from case studies to models; from local to national scale), some top-down initiatives are also in order, such as the construction of a model to estimate the inpact of different macroeconomic policies and growth trajectories on land use. We believe science and society in Brazil will benefit of the coexistence of bottom-up and top-down integrative approaches.

Biodiversity↗
PubMed2006

Integrating evidence-based practice in the child mental health agency: a template for clinical and organizational change.

This article describes a linked set of activities designed to address the present "science-to-service" gap in evidence-based practice from the perspective of the nonprofit child mental health agency: (a) implementing "systems-of-care" principles; (b) logic modeling; (c) strategic partnerships with external researchers; (d) selective, in-depth program evaluation; (e) critical comparison with a limited number of evidence-based practice models of national significance; and (f) internal and external dissemination activities oriented to evidence-based practice. Implications are drawn both for continuous quality improvement of existing clinical services and for the potential for agencies to contribute high quality, science-based information to child mental health services, singly and through the future development of a national network of experimenting child mental health agencies.

Child↗