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PubMed1994

Computer education: attitudes and opinions of first-year medical students.

Students' attitudes toward medical informatics were evaluated with self-administered questionnaires, answered by 140 (77%) first-year medical and dental students. Fourteen per cent classified their computer literacy as negligible and 49% as deficient. Ninety-six per cent had used a computer before and 59% used one regularly. Nineteen per cent had computer education in secondary school and a further 16% attended courses given by a computer company. Only 16% read regularly about informatics. These results are similar to those observed in more industrialized countries, except that high-school education is more deficient. To 93% of these students, computer literacy is important for doctors, and to 85% computers may be very useful in many areas of health care. In the opinion of 66% of students, the computer-based patient record will be available within the next 3 to 10 years. Women showed lesser computer literacy (77% computer illiteracy to 39% in men), but there were no relevant differences in attitudes, behaviour and beliefs towards medical informatics between gender, for the same level of computer literacy. Computer education in the undergraduate curriculum was demanded by 92%, and 75% of these preferred an elective course. Weekly hours suggested for lectures should be 1 (54%) or 2 (42%), and for hands-on practice 2 (54%) or 4 (31%) hours. The curriculum should include medical applications (83% of students), information science theory and technology (44%), micro-informatics (44%), bibliographic database search (27%), programming languages (23%) and statistical packages (23%). Gender, computer literacy or course did not correlate significantly with students' opinions about the contents of undergraduate education.

Attitude of Health Personnel↗
PubMed2004

Heart to Heart: a computerized decision aid for assessment of coronary heart disease risk and the impact of risk-reduction interventions for primary prevention.

Heart to Heart is a computer-based decision aid for patients and providers that provides personalized, evidence-based information about coronary heart disease (CHD) risk and potential risk-reducing interventions. To develop Heart to Heart, the authors used Framing-ham risk equations and systematic reviews of risk-reducing interventions. The Web version was programmed using PHP: Hypertext Processor, a Web-based programming language, and has separate interfaces for providers and patients. The authors subsequently developed a modified version for personal digital assistants. Heart to Heart uses information about a patient's CHD risk factors (age, gender, total and high-density lipoprotein cholesterol levels, diabetes, smoking, systolic blood pressure, and left ventricular hypertrophy) to calculate risk of total CHD events over 5 or 10 years. Patients and providers can then examine the effect of introducing one or more risk-reducing interventions (aspirin, lipid-lowering drug therapy, antihypertensive medication, or smoking cessation) on the patient's CHD risk. Future research will be directed to determining whether Heart to Heart can improve utilization of effective CHD risk-reducing interventions.

Adult↗
PubMed1984

Pacemaker architecture: a pacemaker with an attached computer or a computer with an attached pacemaker.

Microprocessors have a major impact on cardiac pacemaker technology. The development of adaptive systems capable of responding to physiologic variables will ultimately improve the care of the individual patient. However, in order to minimize power drain, it will be necessary to incorporate certain functions into the hardware outside the microprocessor. In addition, specifically designed program languages may indeed become necessary.

Cardiac Pacing, Artificial↗
PubMed2004

A novel robotic system for joint biomechanical tests: application to the human knee joint.

The objectives of the work reported in this article were to develop a novel 6-degree-of-freedom (DOC) robotic system for knee joint biomechanics, to complete a hybrid force-position control scheme, to evaluate the system performance, and to demonstrate a combined loading test. The manipulator of the system utilizes two mechanisms; the upper mechanism has two translational axes and three rotational axes while the lower mechanism has only a single translational axis. All axes were driven with AC servo-motors. This unique configuration results in a simple kinematic description of manipulator motion. Jacobian transformation was used to calculate both the displacement and force/moment, which allowed for a hybrid control of the displacement of, and force/moment applied to, the human knee joint. The control and data acquisition were performed on a personal computer in the C-language programming environment with a multi-tasking operating system. Preliminary tests revealed that the clamp-to-clamp compliance of the system was smaller in the vertical (Z) and longitudinal (Y) directions (0.001 mm/N) than in lateral (X) direction (0.003 mm/N). The displacement error under the application of 500 N of load was smallest in the vertical direction (0.001 +/- 0.003 mm (mean +/- SD), and largest in the lateral direction (0.084 +/- 0.027 mm). Using this test system, it was possible to simulate multiple loading conditions in a human knee joint in which a cyclic anterior force was applied together with a coupled, joint compressive force, while allowing natural knee motion. The developed system seems to be a useful tool for studies of knee joint biomechanics.

Biomechanical Phenomena↗
PubMed2005

Simultaneous optimization of sequential IMRT plans.

Radiotherapy often comprises two phases, in which irradiation of a volume at risk for microscopic disease is followed by a sequential dose escalation to a smaller volume either at a higher risk for microscopic disease or containing only gross disease. This technique is difficult to implement with intensity modulated radiotherapy, as the tolerance doses of critical structures must be respected over the sum of the two plans. Techniques that include an integrated boost have been proposed to address this problem. However, clinical experience with such techniques is limited, and many clinicians are uncomfortable prescribing nonconventional fractionation schemes. To solve this problem, we developed an optimization technique that simultaneously generates sequential initial and boost IMRT plans. We have developed an optimization tool that uses a commercial treatment planning system (TPS) and a high level programming language for technical computing. The tool uses the TPS to calculate the dose deposition coefficients (DDCs) for optimization. The DDCs were imported into external software and the treatment ports duplicated to create the boost plan. The initial, boost, and tolerance doses were specified and used to construct cost functions. The initial and boost plans were optimized simultaneously using a gradient search technique. Following optimization, the fluence maps were exported to the TPS for dose calculation. Seven patients treated using sequential techniques were selected from our clinical database. The initial and boost plans used to treat these patients were developed independently of each other by dividing the tolerance doses proportionally between the initial and boost plans and then iteratively optimizing the plans until a summation that met the treatment goals was obtained. We used the simultaneous optimization technique to generate plans that met the original planning goals. The coverage of the initial and boost target volumes in the simultaneously optimized plans was equivalent to the independently optimized plans actually used for treatment. Tolerance doses of the critical structures were respected for the plan sum; however, the dose to critical structures for the individual initial and boost plans was different between the simultaneously optimized and the independently optimized plans. In conclusion, we have demonstrated a method for optimization of initial and boost plans that treat volume reductions using the same dose per fraction. The method is efficient, as it avoids the iterative approach necessitated by currently available TPSs, and is generalizable to more than two treatment phases. Comparison with clinical plans developed independently suggests that current manual techniques for planning sequential treatments may be suboptimal.

Algorithms↗
PubMed1996

A simulation of microbial competition in the human colonic ecosystem.

Many investigations of the interactions of microbial competitors in the gastrointestinal tract used continuous-flow anaerobic cultures. The simulation reported here was a deterministic 11-compartment model coded by using the C programming language and based on parameters from published in vitro studies and assumptions were data were unavailable. The resource compartments were glucose, lactose and sucrose, starch, sorbose, and serine. Six microbial competitors included indigenous nonpathogenic colonizers of the human gastrointestinal tract (Escherichia coli, Enterobacter aerogenes, Bacteroids ovatus, Fusobacterium varium, and Enterococcus faecalis) and the potential human enteropathogen Salmonella typhimurium. Flows of carbon from the resources to the microbes were modified by resource and space controls. Partitioning of resources to the competitors that could utilize them was calculated at each iteration on the basis of availability of all resources by feeding preference functions. Resources did not accumulate during iterations of the model. The results of the computer simulation of microbial competition model and for various modifications of the model. The results were based on few measured parameters but may be useful in the design of user-friendly software to aid researchers in defining and manipulating the microbial ecology of colonic ecosystems as relates to food-borne disease.

Carbohydrates↗
PubMed1994

Model-based compartmental analyses in nutrition research.

Kinetic tracer studies have been used extensively in understanding digestion, absorption, and whole-body metabolism of nutrients. Optimal interpretation of changes in tracer levels over time and movement across body pools often requires sophisticated data analysis. The use of model-based compartmental analysis (MCA) can yield more detailed quantitative and predictive information concerning system dynamics, compared with direct stochastic approaches. With MCA, tracer and tracee data from both experimental and literature values are fit to a model that best approximates the system on the basis of experimental data at hand. The number of compartments of the model is determined by the shape of the curve fit to the tracee and tracer data and by literature information. On this basis, MCA can yield information about compartment numbers and sizes, fractional and net turnover, as well as catabolic and synthetic rates. PC-based MCA programs are now available. Whereas earlier editions required use of a programming language, the most recent versions being developed are completely menu driven. Model-based compartmental analyses thus represent important biotechnological advances permitting maximal interpretation of kinetic data in nutrition research.

Animal Nutritional Physiological Phenomena↗
PubMed2000

The Ensemble/Legacy Chimera extension: standardized user and programmer interface to molecular Ensemble data and Legacy modeling programs.

Ensemble/Legacy is a toolkit extension of the Object Technology Framework (OTF) that exposes an object oriented interface for accessing and manipulating ensembles (collections of molecular conformations that share a common chemical topology) and driving Legacy programs (such as MSMS, AMBER, X-PLOR, CORMA/MARDIGRAS, Dials and Windows, and CURVES). Ensemble/Legacy provides a natural programming interface for running Legacy programs on ensembles of molecules and accessing the resulting data. Using the OTF reduces the time cost of developing a new library to store and manipulate molecular data and also allows Ensemble/Legacy to integrate into the Chimera visualization program. The extension to Chimera exposes the Legacy functionality using a graphical user interface that greatly simplifies the process of modeling and analyzing conformational ensembles. Furthermore, all the C++ functionality of the Ensemble/Legacy toolkit is "wrapped" for use in the Python programming language. More detailed documentation on using Ensemble/Legacy is available online (http:¿picasso.nmr.ucsf.edu/dek/ensemble. html).

Computer Graphics↗
PubMedDate not supplied

Informatics in radiology (infoRAD): NeatVision: visual programming for computer-aided diagnostic applications.

A free visual programming-based image analysis development environment for medical imaging applications called NeatVision was developed to provide high-level access to a wide range of image processing algorithms through a well-defined, easy-to-use graphical interface. The system contains over 300 image manipulation, processing, and analysis algorithms. For more advanced users, an upgrade path is provided to extend the core library with use of the developer's interface, giving users access to additional plug-in features, automatic source code generation, compilation with full error feedback, and dynamic algorithm updates. NeatVision was designed to allow users at all levels of expertise to focus on the computer vision design task for computer-aided diagnostic (CAD) applications rather than the subtleties of a particular programming language. The environment allows the designers of image analysis-based CAD techniques to implement their ideas in a dynamic and straightforward manner. Both NeatVision standard and developer's versions can be downloaded free of charge from the Internet and can run on a variety of computer platforms.

Diagnosis, Computer-Assisted↗
PubMedDate not supplied

Collaboration system for radiology workstations.

Consultation between radiologists and referring physicians is part of routine medical practice. Nevertheless, a typical picture archiving and communication system contains no provision that will allow this critical interaction to occur on-line. The authors describe an image viewing system designed for real-time interactive consultation over the Internet. The system has two main components: an image viewer and a collaboration server. The image viewer connects to the collaboration server over an Internet-compatible network. Once the image viewer is connected, its display can be synchronized with that of another connected image viewer, so that radiologists can point out image findings and diagnoses in real time to remotely located physicians. The image viewer can retrieve images from any DICOM-compatible archive. In addition to standard image manipulation functions, the image viewer contains a new user interface for image annotation. Developed specifically for medical imaging, this user interface is activated by mouse actions instead of conventional on-screen controls, greatly improving the ease with which annotations can be created. The collaboration system is based on a simple yet flexible programming interface that can be readily generalized to other types of collaborative applications. The system was developed with the Java programming language because of Java's integrated support of Internet-compatible networking capabilities.

Humans↗
PubMedDate not supplied

The quick machine--a mathematical model for the extrinsic activation of coagulation.

The present paper describes a mathematical model of the kinetics of the extrinsic coagulation cascade in vitro. The coagulation factors FI, FII, FV, FVII, FX, heparin and antithrombin III (ATIII) as well as soluble fibrin polymers are considered. The effect of single-factor deficiencies of the factors II, V, VII and X, diseases like hypo- and dysfibrinogenaemia, hepatic insufficiency, inhibited polymerisation by degradation products, heparin therapy with and without ATIII deficiency and coumarin therapy on prothrombin time can be portrayed. Physiology of coagulation is represented in a dynamic mathematical model as a differential equation system. The model is based on three reaction types: enzymatic cleavage, complex formation and polymerisation. The model was implemented in a continuous simulation program on a personal computer using the Pascal programming language. Unknown rate constants were estimated by chi 2 fit. Prothrombin time calculated by the model was compared to the training set of 20 plasma samples. In most but not all cases the model harmonized quite well with the coagulometric data.

Blood Coagulation↗
PubMed1999

Visualizing evolutionary activity of genotypes.

We introduce a method for visualizing evolutionary activity of genotypes. Following a proposal of Bedau and Packard [11], we define a genotype's evolutionary activity in terms of the history of its concentration in the evolving population. To visualize this evolutionary activity we graph the distribution of evolutionary activity in the population of genotypes as a function of time. Adaptively significant genotypes trace a salient line or "wave" in these graphs. The quality of these waves indicates a variety of neutral variation, and random genetic drift. We apply this method in an evolutionary model of self-replicating assembly language programs competing for room in a two-dimensional space. Comparison with fitness graphs and with a nonadaptive analogue of this model shows how this method highlights adaptively significant events.

Biological Evolution↗
PubMedDate not supplied

Cost-effectiveness analysis of treatments for chronic disease: using R to incorporate time dependency of treatment response.

When constructing decision-analytic models to evaluate the cost-effectiveness of alternative treatments, we often need to extrapolate beyond the available experimental data, as these typically relate to a limited period starting from the initiation of a new treatment or the diagnosis of the current disease state. We may also be required to extrapolate beyond the available experimental evidence to compare potential treatment sequences. Markov models are often used for this extrapolation. These models have the defining assumption that future transition probabilities are independent of past transitions. This means that, in general, transition probabilities cannot be conditional of the time spent in a given state. Where data exist to show that the risks of transition are conditional on the time spent in the treatment state, the simplifying Markov assumption can result in a loss in the model's "face validity," and misleading results might be generated. Several methods are available to incorporate time dependency into transition probabilities based on standard methods and software. These include the inclusion of tunnel states in Markov models and patient-level simulation, where a series of individual patients are simulated. This article considers the features and limitations of these methods and also describes a novel approach to building time dependency into a Markov model by incorporating an additional time dimension resulting in a "semi-Markov" model. An example of the implementation of such a model, using the R statistical programming language, is illustrated using a cost-effectiveness model for new epilepsy therapies.

Chronic Disease↗
PubMed2005

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

Algorithms↗
PubMed2005

Automatic extraction of candidate nomenclature terms using the doublet method.

BACKGROUND: New terminology continuously enters the biomedical literature. How can curators identify new terms that can be added to existing nomenclatures? The most direct method, and one that has served well, involves reading the current literature. The scholarly curator adds new terms as they are encountered. Present-day scholars are severely challenged by the enormous volume of biomedical literature. Curators of medical nomenclatures need computational assistance if they hope to keep their terminologies current. The purpose of this paper is to describe a method of rapidly extracting new, candidate terms from huge volumes of biomedical text. The resulting lists of terms can be quickly reviewed by curators and added to nomenclatures, if appropriate. The candidate term extractor uses a variation of the previously described doublet coding method. The algorithm, which operates on virtually any nomenclature, derives from the observation that most terms within a knowledge domain are composed entirely of word combinations found in other terms from the same knowledge domain. Terms can be expressed as sequences of overlapping word doublets that have more specific meaning than the individual words that compose the term. The algorithm parses through text, finding contiguous sequences of word doublets that are known to occur somewhere in the reference nomenclature. When a sequence of matching word doublets is encountered, it is compared with whole terms already included in the nomenclature. If the doublet sequence is not already in the nomenclature, it is extracted as a candidate new term. Candidate new terms can be reviewed by a curator to determine if they should be added to the nomenclature. An implementation of the algorithm is demonstrated, using a corpus of published abstracts obtained through the National Library of Medicine's PubMed query service and using "The developmental lineage classification and taxonomy of neoplasms" as a reference nomenclature. RESULTS: A 31+ Megabyte corpus of pathology journal abstracts was parsed using the doublet extraction method. This corpus consisted of 4,289 records, each containing an abstract title. The total number of words included in the abstract titles was 50,547. New candidate terms for the nomenclature were automatically extracted from the titles of abstracts in the corpus. Total execution time on a desktop computer with CPU speed of 2.79 GHz was 2 seconds. The resulting output consisted of 313 new candidate terms, each consisting of concatenated doublets found in the reference nomenclature. Human review of the 313 candidate terms yielded a list of 285 terms approved by a curator. A final automatic extraction of duplicate terms yielded a final list of 222 new terms (71% of the original 313 extracted candidate terms) that could be added to the reference nomenclature. CONCLUSION: The doublet method for automatically extracting candidate nomenclature terms can be used to quickly find new terms from vast amounts of text. The method can be immediately adapted for virtually any text and any nomenclature. An implementation of the algorithm, in the Perl programming language, is provided with this article.

Abstracting and Indexing↗
PubMed2000

Accessing and distributing EMBL data using CORBA (common object request broker architecture).

BACKGROUND: The EMBL Nucleotide Sequence Database is a comprehensive database of DNA and RNA sequences and related information traditionally made available in flat-file format. Queries through tools such as SRS (Sequence Retrieval System) also return data in flat-file format. Flat files have a number of shortcomings, however, and the resources therefore currently lack a flexible environment to meet individual researchers' needs. The Object Management Group's common object request broker architecture (CORBA) is an industry standard that provides platform-independent programming interfaces and models for portable distributed object-oriented computing applications. Its independence from programming languages, computing platforms and network protocols makes it attractive for developing new applications for querying and distributing biological data. RESULTS: A CORBA infrastructure developed by EMBL-EBI provides an efficient means of accessing and distributing EMBL data. The EMBL object model is defined such that it provides a basis for specifying interfaces in interface definition language (IDL) and thus for developing the CORBA servers. The mapping from the object model to the relational schema in the underlying Oracle database uses the facilities provided by PersistenceTM, an object/relational tool. The techniques of developing loaders and 'live object caching' with persistent objects achieve a smart live object cache where objects are created on demand. The objects are managed by an evictor pattern mechanism. CONCLUSIONS: The CORBA interfaces to the EMBL database address some of the problems of traditional flat-file formats and provide an efficient means for accessing and distributing EMBL data. CORBA also provides a flexible environment for users to develop their applications by building clients to our CORBA servers, which can be integrated into existing systems.

Computational Biology↗
PubMed2003

Evolving strategies for the incorporation of bioinformatics within the undergraduate cell biology curriculum.

Recent advances in genomics and structural biology have resulted in an unprecedented increase in biological data available from Internet-accessible databases. In order to help students effectively use this vast repository of information, undergraduate biology students at Drake University were introduced to bioinformatics software and databases in three courses, beginning with an introductory course in cell biology. The exercises and projects that were used to help students develop literacy in bioinformatics are described. In a recently offered course in bioinformatics, students developed their own simple sequence analysis tool using the Perl programming language. These experiences are described from the point of view of the instructor as well as the students. A preliminary assessment has been made of the degree to which students had developed a working knowledge of bioinformatics concepts and methods. Finally, some conclusions have been drawn from these courses that may be helpful to instructors wishing to introduce bioinformatics within the undergraduate biology curriculum.

Biology↗