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PubMed1987

Computer instruction as part of a course on analytic medicine for first-year students.

The Medical University of South Carolina integrated instruction in information science and computer technology into a required freshman-level course. Analytic and Community Medicine. The advantages of this placement in the curriculum are two-fold. First, the course provides an opportunity to integrate computer methodology with clinically relevant topics such as medical decision-making. This integration enhances the students' view of the computer as a useful tool that can aid the physician in the practice of medicine. Course organizers are convinced that the success of the first offering is attributable to this integration. Second, the instruction comes early in the medical education process and allows the concepts learned to be utilized throughout the students' medical school careers. The degree to which these concepts and methods are actually utilized by students will depend upon the degree of reinforcement of these ideas in the clinical years and residency. Thus, faculty members must act as role models who not only acknowledge the importance of mastering the use of computers in medicine but also manifest those skills.

Community Medicine↗
PubMed2001

Analysis of complex decision-making processes in health care: cognitive approaches to health informatics.

Decision making by health care professionals is often complicated by the need to integrate ill-structured, uncertain, and potentially conflicting information from various sources. In this paper cognitive approaches to the study of decision making are presented within the context of a variety of complex health care applications. In recent years it has become increasingly accepted that in order to build information systems that can support complex decision making it will be necessary to more fully understand human decision-making processes. Methodological approaches are described that aim to explicate the decision making and reasoning skills of subjects as they perform activities involving the processing of complex information. The paper begins by presenting the theoretical foundations for cognitive analyses of decision making, including discussion of major approaches to the study of decision making in a range of real-world domains, including medicine. Applications of cognitive approaches are then illustrated, including a description of a study in which subjects were asked to "think aloud" in providing treatment decisions for complex medical cases. The resulting protocols were then analyzed for subjects' use of decision strategies and problems in reasoning. Extension of cognitive approaches to the study of group decision-making processes is also described. Recent approaches are discussed which borrow from advances in the study of human-computer interaction and which utilize video analysis of decision-making activities involving information technologies. Using these approaches it has been found that health care information systems, such as computerized patient record systems, may have inadvertent effects on human decision making. Implications of a cognitive approach to improving our understanding of complex decision making are discussed in the context of developing appropriate computer-based decision support for both individuals and groups.

Cognitive Science↗
PubMed1986

Computers in dentistry.

Traditionally, each professional school has developed its own course or department of health care informatics. We may find it more efficient and productive to establish a department of Medical Informatics to serve all health science colleges. Therefore the initial costs would be reduced and the common knowledge bank would be greatly increased. In a position paper written for the Association of Academic Health Centers lies the detailed plans for the establishment of an integrated health sciences center computer resource. The inclusion of computer courses in the curriculum can be summarized in the following action step. The chief administrative officer of the academic health center should facilitate the work of the deans of the schools of the health professions in convening faculty task forces that will address the introduction of computer literacy and computer applications in health care to the curricula. Although dental informatics is still in its infancy, we must lay a solid foundation for the controlled growth and development of this field of dental science. The problems encountered in developing a course in dental informatics are not unique to this one area. All specialties of health care are grappling with the questions posed by medical informaticians. Although each specialty has its own needs and requirements, the basic underlying principles of medical informatics remains the same. The knowledge we can gain by the exchange of experiences between all fields can greatly increase the speed and accuracy of development. The primary goal of computer literacy in dental education should be to prepare our students for the changing practice environment of the future.

Computer Literacy↗
PubMed1989

[Hygienic substantiation of the system of education based on information science and technology in senior classes using computers].

The conducted studies showed that the degree of fatigue of the 10-grade students at the lessons on the basics of information science and computing technology was determined by the duration of work with video terminals. Thus, the general length of work with displays in the IIId class should be limited by 30 min: 20 min at the beginning of the lesson and then 10 min later the complex of physical exercises for general and visual fatigue unloading. More prolonged with displays resulted in deterioration of students'++ body functional state and decrease of their work capacity.

Adolescent↗
PubMed2004

Training the next generation of informaticians: the impact of "BISTI" and bioinformatics--a report from the American College of Medical Informatics.

In 2002-2003, the American College of Medical Informatics (ACMI) undertook a study of the future of informatics training. This project capitalized on the rapidly expanding interest in the role of computation in basic biological research, well characterized in the National Institutes of Health (NIH) Biomedical Information Science and Technology Initiative (BISTI) report. The defining activity of the project was the three-day 2002 Annual Symposium of the College. A committee, comprised of the authors of this report, subsequently carried out activities, including interviews with a broader informatics and biological sciences constituency, collation and categorization of observations, and generation of recommendations. The committee viewed biomedical informatics as an interdisciplinary field, combining basic informational and computational sciences with application domains, including health care, biological research, and education. Consequently, effective training in informatics, viewed from a national perspective, should encompass four key elements: (1). curricula that integrate experiences in the computational sciences and application domains rather than just concatenating them; (2). diversity among trainees, with individualized, interdisciplinary cross-training allowing each trainee to develop key competencies that he or she does not initially possess; (3). direct immersion in research and development activities; and (4). exposure across the wide range of basic informational and computational sciences. Informatics training programs that implement these features, irrespective of their funding sources, will meet and exceed the challenges raised by the BISTI report, and optimally prepare their trainees for careers in a field that continues to evolve.

Computational Biology↗
PubMed2004

Tackling the challenges of interdisciplinary bioscience.

The ultimate goal for biology is to become a science that formulates our understanding of subcellular, cellular and multicellular systems in terms of quantitative, holistic models that are underpinned by the rigorous principles of the physical sciences and mathematics. This can only be achieved through interdisciplinary research that draws heavily on the expertise and technologies of the physical sciences, engineering, computation and mathematics. Here, I discuss the benefits and challenges (both intellectual and practical) of interdisciplinary bioscience.

Biological Science Disciplines↗
PubMed2000

New industrial training program for interns and postdoctoral fellows.

Pharmaceutical industry research managers consistently have difficulty finding job candidates trained to address industrial research projects. The current situation is even worse than usual because of high demand for research scientists, particularly those trained in solid phase synthesis, computational chemistry, and informatics. Network Science Corp., Chemical Computing Group, and pharmaceutical research groups are creating a website to assist students in gaining experience as industrial interns or postdoctoral fellows.

Drug Industry↗
PubMed1980

Computer-simulated laboratory experiments in food science. II. Evaluation of the model in use.

Evidence obtained in this study indicates that computer simulations can be a successful method of teaching foods or can replace laboratory experiences. For nine of eleven attitudinal test items, students' attitudes became more positive concerning the value of the course in which computer simulations were used. On the achievement test, seventeen of the twenty-five questions revealed that significant learning (p of less than or equal to 0.05) occurred when the simulations were integrated into a foods course. These students seemed to do well and to like this method of instruction. The advantages of these computer simulations are that students can be motivated to learn and solve problems.

Computer-Assisted Instruction↗
PubMed2003

Criteria for classification of medical information.

Medical information, which is the central notion in medical informatics, covers a large scale of structures and forms. Several classifications are possible and two criteria have been used in this paper: structural level and informational level. According to structural level we can distinguish three major areas: bioinformatics and neuroinformatics for molecular/cellular level, medical informatics for individual level and health informatics for community level and healthcare units. According to informational level the terms of data and knowledge are used and the representative information for each structural level is analysed also from this point of view: Finally, information transfer from living systems to computers is also seen through the structural point of view.

Biological Science Disciplines↗
PubMed2003

Medical education as a science: the quality of evidence for computer-assisted instruction.

OBJECTIVE: A marked increase in the number of computer programs for computer-assisted instruction in the medical sciences has occurred over the past 10 years. The quality of both the programs and the literature that describe these programs has varied considerably. The purposes of this study were to evaluate the published literature that described computer-assisted instruction in medical education and to assess the quality of evidence for its implementation, with particular emphasis on obstetrics and gynecology. STUDY DESIGN: Reports published between 1988 and 2000 on computer-assisted instruction in medical education were identified through a search of MEDLINE and Educational Resource Identification Center and a review of the bibliographies of the articles that were identified. Studies were selected if they included a description of computer-assisted instruction in medical education, regardless of the type of computer program. Data were extracted with a content analysis of 210 reports. The reports were categorized according to study design (comparative, prospective, descriptive, review, or editorial), type of computer-assisted instruction, medical specialty, and measures of effectiveness. RESULTS: Computer-assisted instruction programs included online technologies, CD-ROMs, video laser disks, multimedia work stations, virtual reality, and simulation testing. Studies were identified in all medical specialties, with a preponderance in internal medicine, general surgery, radiology, obstetrics and gynecology, pediatrics, and pathology. Ninety-six percent of the articles described a favorable impact of computer-assisted instruction in medical education, regardless of the quality of the evidence. Of the 210 reports that were identified, 60% were noncomparative, descriptive reports of new techniques in computer-assisted instruction, and 15% and 14% were reviews and editorials, respectively, of existing technology. Eleven percent of studies were comparative and included some form of assessment of the effectiveness of the computer program. These assessments included pre- and posttesting and questionnaires to score program quality, perceptions of the medical students and/or residents regarding the program, and impact on learning. In one half of these comparative studies, computer-assisted instruction was compared with traditional modes of teaching, such as text and lectures. Six studies compared performance before and after the computer-assisted instruction. Improvements were shown in 5 of the studies. In the remainder of the studies, computer-assisted instruction appeared to result in similar test performance. Despite study design or outcome, most articles described enthusiastic endorsement of the programs by the participants, including medical students, residents, and practicing physicians. Only 1 study included cost analysis. Thirteen of the articles were in obstetrics and gynecology. CONCLUSION: Computer-assisted instruction has assumed to have an increasing role in medical education. In spite of enthusiastic endorsement and continued improvements in software, few studies of good design clearly demonstrate improvement in medical education over traditional modalities. There are no comparative studies in obstetrics and gynecology that demonstrate a clear-cut advantage. Future studies of computer-assisted instruction that include comparisons and cost assessments to gauge their effectiveness over traditional methods may better define their precise role.

Computer-Assisted Instruction↗
PubMed2002

Computationally intensive econometrics using a distributed matrix-programming language.

This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy-to-use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well-known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; and (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.

Computer Communication Networks↗
PubMed2006

Efficient numerical algorithm for multiphase field simulations.

Phase-field models have emerged as a successful class of models in a wide variety of applications in computational materials science. Multiphase field theories, as a subclass of phase-field theories, have been especially useful for studying nucleation and growth in polycrystalline materials. In theory, an infinite number of phase-field variables are required to represent grain orientations in a rotationally invariant free energy. However, limitations on available computational time and memory have restricted the number of phase-field variables used in the simulations. We present an approach by which the time and memory requirements are drastically reduced relative to standard algorithms. The proposed algorithm allows us the use of an unlimited number of phase-field variables to perform simulations without the associated burden on computational time or memory. We present the algorithm in the context of coalescence free grain growth.

Journal Article↗