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PubMed2000

Applications of computer-aided learning in biomedical sciences: considerations in design and evaluation.

Multimedia computer-aided learning (CAL) is an area that has become increasingly prevalent in biomedical science. Here we describe the advances that have taken place in the computing industry that have led to this trend. We also outline areas within the subject of biomedical science that can most benefit from using multimedia CAL as a teaching aid. Furthermore, issues concerning the design of CAL (i.e. iterative design, structure, development tools) are discussed. As the evaluation of CAL is an essential part of the iterative design process, we look at new approaches to evaluation that have emerged in response to the superficial focus on usability that many evaluations take.

Computer-Assisted Instruction↗
PubMed1980

Computer-simulated laboratory experiments in food science. I. The model.

A computer model and instructional material provide the student with the opportunity to learn basic information and gain expertise in solving problems which occur in foods. The model covers twenty-five simulations over a range of food types, permitting a variety of experiments of differing complexity. The student is assigned a problem or activity which may be partially or completely answered by using one of the simulations. The simulations give answers to a series of treatments and tests, properties, recipes, characteristics, and/or sensory parameters being investigated.

Computer-Assisted Instruction↗
PubMed1992

PC CLIN-SIM: a toolbook based clinical simulation environment.

The Departments of Computer Medicine, Health Care Sciences, Medicine, and Electrical Engineering & Computer Science at the George Washington University have joined forces to create a clinical simulation program. The purpose of this program is to provide experience in the management of complex patient populations (eg geriatrics). A number of simulation programs are available commercially, however none provide adequate geriatric content, or were deemed to lack functionality important to the developers. The immediate goal of this effort was to create a computer-based, core curriculum in geriatric medicine for medical and allied health students. The curriculum includes case simulations linked to a comprehensive reference database. The development objectives were to create an intuitive, friendly, consistent user interface which could serve as a shell for additional content areas. In order to increase fidelity, free text entry and time simulation were included.

Computer Graphics↗
PubMed2002

Human-computer interaction: psychological aspects of the human use of computing.

Human-computer interaction (HCI) is a multidisciplinary field in which psychology and other social sciences unite with computer science and related technical fields with the goal of making computing systems that are both useful and usable. It is a blend of applied and basic research, both drawing from psychological research and contributing new ideas to it. New technologies continuously challenge HCI researchers with new options, as do the demands of new audiences and uses. A variety of usability methods have been developed that draw upon psychological principles. HCI research has expanded beyond its roots in the cognitive processes of individual users to include social and organizational processes involved in computer usage in real environments as well as the use of computers in collaboration. HCI researchers need to be mindful of the longer-term changes brought about by the use of computing in a variety of venues.

Attitude to Computers↗
PubMed1979

Effectiveness of instructional computers in teaching basic medical sciences.

The present study was designed to investigate the effectiveness of computer-based PLATO IV basic medical science lessons. Effectiveness was operationalized in terms of increased performance on basic medical science examinations for those medical students who had used the lessons when compared to those students who had not. Usage of the PLATO lessons was quantified as 'minutes of use' of the relevant lessons. Data were gathered in 1976-77 from first-year medical students at two sites, both under the auspices of one college of medicine. Usage of PLATO lessons and subsequent performance on three subtests from three different examinations were analysed. The findings from the current study offer encouragement that use of PLATO basic medical science materials contribute to increased performance on subsequent examinations.

Computer-Assisted Instruction↗
PubMed2000

Computer applications in biomolecular sciences. Part 2: bioinformatics and genome projects.

This article defines and describes some of the basics of bioinformatics and projects aimed at sequencing entire genomes. Emphasis is placed on some of the ways in which the primary structures of nucleic acids and proteins may be investigated and analysed to gain meaningful biological information using computers and appropriate software. The importance of the world wide net and access to it is given prominence, particularly in bioinformatics research and teaching.

Journal Article↗
PubMed2003

CSCW-based system development methodology for health-care information systems.

Health-care organizations are now moving toward integrated delivery systems to provide high-quality care, as they are being held to an ever-increasing scope of accountabilities. Distributed applications such as telemedicine and electronic patient records (EPR) are seen as key requirements for the future to deliver cost effective and high-quality health-care services. This initiative would provide dynamic environments for health professionals to access patient information and thereby increase the decision-making capacities on patient care procedures. Although telemedicine applications and EPR contribute to the improvement of healthcare services, poor communication mechanisms and practices negatively impact on quality of service (QoS) in teamwork environments of patient care. Awareness and responsiveness are becoming important factors in dynamic group collaborative work environments in healthcare facilities. This paper reports on a detailed case study of group communication patterns in a patient service environment. Further, an ethnographic approach that addresses group communications patterns, identifies tools and techniques in light of Computer-Supported Collaborative Work (CSCW), which requires the application of a number of disciplines including sociology, organizational science, psychology, and computer science. In cooperative work environments, it is important to understand the activities of others for human interaction and communication in general. This is very important for future development of CSCW-based distributed architectures that focus on the challenges of improving QoS in healthcare environments.

Computer Communication Networks↗
PubMed1986

Computers as learning resources in the health sciences: impact and issues.

Starting with two computer terminals in 1972, the Health Sciences Learning Resources Center of the University of Minnesota Bio-Medical Library expanded its instructional facilities to ten terminals and thirty-five microcomputers by 1985. Computer use accounted for 28% of total center circulation. The impact of these resources on health sciences curricula is described and issues related to use, support, and planning are raised and discussed. Judged by their acceptance and educational value, computers are successful health sciences learning resources at the University of Minnesota.

Computer-Assisted Instruction↗
PubMedDate not supplied

A descriptive analysis of National Library of Medicine-funded medical informatics training programs and the career choices of their graduates.

The initial 13 National Library of Medicine-supported medical informatics training programs and their graduates were studied to determine the program objectives, trainee selection factors, and curriculum components of the programs and the backgrounds and career choices of the trainees. All 13 programs and over 60% of the available population of trainees were studied. The analysis indicated that 1) the major objective was to train individuals in the applications of computer and information science to medicine: 2) the most frequent selection factor was the MD degree; 3) course work in computer science and a research project were the most common curriculum components; 4) 52% of the graduates selected academic careers; and 5) personal reasons most frequently influenced career choices. There is now a baseline of data that can be used in future studies.

Career Choice↗
PubMed2006

Computational intelligence in earth sciences and environmental applications: issues and challenges.

This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The issues of data quality, selection of the error function, incorporation of the predictive learning methods into the existing modeling frameworks, expert knowledge, model uncertainty, and other application-domain specific problems are discussed. A brief overview of the papers in the Special Issue is provided, followed by discussion of open issues and directions for future research.

Artificial Intelligence↗
PubMed2005

Artificial intelligence in hematology.

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Artificial Intelligence↗
PubMedDate not supplied

Some neural network applications in environmental sciences. Part II: advancing computational efficiency of environmental numerical models.

A new generic neural network (NN) application-improving computational efficiency of certain processes in numerical environmental models-is considered. This approach can be used to accelerate the calculations and improve the accuracy of the parameterizations of several types of physical processes which generally require computations involving complex mathematical expressions, including differential and integral equations, rules, restrictions and highly nonlinear empirical relations based on physical or statistical models. It is shown that, from a mathematical point of view, such parameterizations can usually be considered as continuous mappings (continuous dependencies between two vectors) and, therefore, NNs can be used to replace primary parameterization algorithms. In addition to fast and accurate approximation of the primary parameterization, NN also provides the entire Jacobian for very little computation cost. Four particular real-life applications of the NN approach are presented here: for oceanic numerical models, a NN approximation of the UNESCO equation of state of the sea water (NN for the density of the seawater) and an inversion of this equation (NN for the salinity of the seawater); for atmospheric numerical models, a NN approximation for long wave radiative transfer code; and for wave models, a NN approximation for the nonlinear wave-wave interaction. In all considered applications a significant acceleration of numerical computations has been achieved. The first two of these NN applications have already been implemented in the multi-scale ocean forecast system at NCEP. The NN approach introduced in this paper can provide numerically efficient solutions to a wide range of problems in numerical models where lengthy, complicated calculations, which describe physical, chemical and/or biological processes, must be repeated frequently.

Environment↗
PubMed2004

Mapping topics and topic bursts in PNAS.

Scientific research is highly dynamic. New areas of science continually evolve; others gain or lose importance, merge, or split. Due to the steady increase in the number of scientific publications, it is hard to keep an overview of the structure and dynamic development of one's own field of science, much less all scientific domains. However, knowledge of "hot" topics, emergent research frontiers, or change of focus in certain areas is a critical component of resource allocation decisions in research laboratories, governmental institutions, and corporations. This paper demonstrates the utilization of Kleinberg's burst detection algorithm, co-word occurrence analysis, and graph layout techniques to generate maps that support the identification of major research topics and trends. The approach was applied to analyze and map the complete set of papers published in PNAS in the years 1982-2001. Six domain experts examined and commented on the resulting maps in an attempt to reconstruct the evolution of major research areas covered by PNAS.

Algorithms↗