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PubMed2004

A probabilistic active support vector learning algorithm.

The paper describes a probabilistic active learning strategy for support vector machine (SVM) design in large data applications. The learning strategy is motivated by the statistical query model. While most existing methods of active SVM learning query for points based on their proximity to the current separating hyperplane, the proposed method queries for a set of points according to a distribution as determined by the current separating hyperplane and a newly defined concept of an adaptive confidence factor. This enables the algorithm to have more robust and efficient learning capabilities. The confidence factor is estimated from local information using the k nearest neighbor principle. The effectiveness of the method is demonstrated on real-life data sets both in terms of generalization performance, query complexity, and training time.

Algorithms↗
PubMed1998

[Biological calculation methods and their application in pharmaceutical science].

This article gives an introduction to certain mathematical methods, that were developed with biological processes as model. Three methods are described: clustering and the more recently developed genetic algorithms and neural nets. Mainly the last two methods were applied first outside the medical and biological domain but are now used also in the medical and pharmaceutical sciences. There are many applications in the drug discovery field, but these methods are also becoming increasingly important in other domains of the pharmaceutical sciences (such as pharmaceutical technologies).

Algorithms↗
PubMed1998

Object-oriented analysis and design: a methodology for modeling the computer-based patient record.

The article highlights the importance of an object-oriented analysis and design (OOAD) methodology for the computer-based patient record (CPR) in the military environment. Many OOAD methodologies do not adequately scale up, allow for efficient reuse of their products, or accommodate legacy systems. A methodology that addresses these issues is formulated and used to demonstrate its applicability in a large-scale health care service system. During a period of 6 months, a team of object modelers and domain experts formulated an OOAD methodology tailored to the Department of Defense Military Health System and used it to produce components of an object model for simple order processing. This methodology and the lessons learned during its implementation are described. This approach is necessary to achieve broad interoperability among heterogeneous automated information systems.

Abstracting and Indexing↗
PubMed2001

Computational expansion of genetic networks.

We present a new methodology for computational analysis of gene and protein networks. The aim is to generate new educated hypotheses on gene functions and on the logic of the biological network circuitry, based on gene expression profiles. The framework supports the incorporation of biologically motivated network constraints and rules to improve specificity. Since current data is insufficient for de-novo reconstruction, the method receives as input a known pathway core and suggests likely expansions to it. Network modeling is combinatorial, yet data can be probabilistic. At the heart of the approach are a fitness function which estimates the quality of suggested network expansions given the core and the data, and a specificity measure of the expansions. The approach has been implemented in an interactive software tool called GENESYS. We report encouraging results in preliminary analysis of yeast ergosterol pathway based on transcription profiles. In particular, the analysis suggests a novel ergosterol transcription factor.

Algorithms↗
PubMedDate not supplied

Evaluation of three methodologies for assessing work activity during computer use.

The overall goal of this study was to evaluate three separate methodologies for gathering work activity information among computer users. These methodologies included worker self-report, work sampling, and activity monitoring. A repeated measures design was employed whereby data were collected simultaneously on each subject (n = 51) across three consecutive workdays. Exposure information gathered included keying time, mouse usage, and time spent performing various work tasks (i.e., writing, proofreading, handling documents). Subjects were recruited to represent a wide range of keyboard activity and mouse usage. The study found that worker self-reports overestimated actual keyboard usage by a factor of approximately 1.5 for workers using the keyboard an average of 4 hours per day to a factor of 4 for workers using the keyboard an average of 30 min per day. On average, there was an approximate twofold difference between worker self-reported keying time and that obtained via activity monitoring and work sampling. This trend was similar with regard to time spent using the computer mouse. Worker self-reported mouse usage was approximately twofold higher than that obtained via activity monitoring or work sampling. Self-reported exposure information not only resulted in different estimates, but showed greater variance compared with the other methodologies. The results of this study suggest that the use of worker self-reported exposure information on keying time and mouse usage may not represent an accurate account of time spent performing these tasks. In the context of epidemiological studies work sampling and/or activity monitoring would be more suitable methodologies for obtaining such information.

Adult↗
PubMed1988

Computer-assisted densitometric image analysis in periodontal radiography. A methodological study.

A videobased computer assisted densitometric image analysis (CADIA) system to quantify alveolar bone density changes on standardized dental radiographs was tested. An algorithm was used for grey level correction of a subsequent image to the baseline image. Quantitative information regarding positive and/or negative grey level changes were obtained automatically. Comparison of the ability of CADIA to detect surgically induced bone loss with interpretation of digital subtraction images and conventional radiographic interpretation revealed that CADIA was the most sensitive of the 3 methods, followed by interpretation of digital subtraction images which was considerably more sensitive than conventional radiographic interpretation. CADIA was capable of assessing differences in alveolar bone changes due to periodontal surgery between sites exposed to ostectomy/osteoplasty and control sites and sites exposed to periodontal surgery without ostectomy/osteoplasty. Finally, CADIA was capable of assessing differences in remodeling activity over 4-6 weeks after periodontal surgery between 45 surgical sites and 45 control sites. The system offers an objective method to quantitatively follow alveolar bone density changes over time and appears to be the most sensitive of previously described radiographic interpretation techniques.

Absorptiometry, Photon↗
PubMed2001

Fundamentals of the model behind the COSMOS methodology used for team assessment in simulator training.

Team working is the basic way of working in the control rooms of hazardous technologies and therefore its quality is a safety-relevant issue. In addition to the technological competence it is also crucial for the crews to have the necessary communicational skills. During simulator training these skills can only be improved if the simulator use is embedded in an appropriate setting. To support this skill acquisition a computer-supported methodology called COSMOS (COmputer Supported Method for Operators' Self-assessment) has been developed. With its help more effective communication and more complete shared mental models can be fostered. This paper is a report on the psychological fundamentals and the mathematical model of the COSMOS methodology.

Communication↗
PubMed2003

A meta-analysis of the effectiveness of bibliotherapy for alcohol problems.

There has been increased interest in the use of brief interventions and the delivery of alcohol treatment services through nonspecialist health care settings. One possible resource for reaching untreated individuals is "bibliotherapy," the provision of self-help materials to motivate and guide the process of changing drinking behavior. Research on the effectiveness of self-help materials for problem drinkers has been done for three decades. This report summarizes a meta-analytic review of 22 studies evaluating the effectiveness of such self-help materials. Each study was rated on 12 methodological criteria, and effect sizes of bibliotherapy were computed. The methodological quality of studies was generally high relative to other treatment-outcome studies. Modest support was found for the efficacy of self-help materials in decreasing at-risk and harmful drinking. The weighted mean pre/post-effect size for bibliotherapy was .80 with self-referred individuals seeking help for drinking problems, and .65 for individuals identified through health screening. Between-group comparisons of bibliotherapy with no-intervention controls appear to have a small to medium effect, with a weighted mean effect size of .31 with self-referred drinkers; effect size was more variable in opportunistic interventions based on health screening. Finally, between-group comparisons of effects on drinking of bibliotherapy versus more extensive interventions yielded effect size values near zero. These findings provide support for the cost-effective use of bibliotherapy with problem drinkers seeking such help to reduce their consumption, and to a lesser extent with drinkers who are identified through screening as at risk.

Alcoholism↗
PubMed2004

Medicine without drugs--a new direction for application of nanotechnology.

A working model of direct computer-organism interaction is described. The model is based on the understanding of the ways/modes, by which information is transmitted in the living organism. Information is transmitted in an organism by different ways. Communication between (among) the streams of different modes of information is provided by particular natural mechanisms--transformers and interconnectors. The model suggests that the functions of the cells, organs and systems of an organism can be monitored, controlled and governed directly by means of nano-computers. The application of a computer enables one to provide early diagnostics and successful treatment using specifically designed computer programs instead of, or in conjunction with, medications or surgery. The computer-organism interaction is being achieved through an effective engagement and interaction of the streams of computer generated information with the streams of information naturally transmitted in the organism.

Biotechnology↗
PubMed1998

A multipurpose model of radiology appropriateness criteria.

RATIONALE AND OBJECTIVES: Appropriateness criteria and practice guidelines are being developed in attempts to improve the cost-effectiveness of medical care. The authors sought to make a set of radiology appropriateness criteria usable for education, computer-based decision support, and utilization review. MODEL DEVELOPMENT: Sixty clinical conditions from the American College of Radiology's appropriateness criteria were selected. To make the information more suitable for automation, the names of the imaging procedures were standardized. Indexing terms were assigned to identify clinical conditions and to distinguish between each condition's variants. Semantic relationships between terms were defined. Information about the clinical conditions and variants, radiologic procedures, indexing terms, and relationships was encoded into a standardized language for document interchange. IMPLEMENTATION: The 1,956 rows in the appropriateness criteria tables for the 60 clinical conditions and their 212 variants were mapped into references to 163 distinct imaging procedures. The system's knowledge base included 301 indexing terms and 569 additional terms. CONCLUSION: Radiology appropriateness criteria can be indexed and encoded into a form that facilitates their use and interchange. The use of open, internationally accepted standards is an important step to make such knowledge portable and suitable for integration with evolving computer-based patient record systems.

Computing Methodologies↗
PubMed2004

Biological applications of support vector machines.

One of the major tasks in bioinformatics is the classification and prediction of biological data. With the rapid increase in size of the biological databanks, it is essential to use computer programs to automate the classification process. At present, the computer programs that give the best prediction performance are support vector machines (SVMs). This is because SVMs are designed to maximise the margin to separate two classes so that the trained model generalises well on unseen data. Most other computer programs implement a classifier through the minimisation of error occurred in training, which leads to poorer generalisation. Because of this, SVMs have been widely applied to many areas of bioinformatics including protein function prediction, protease functional site recognition, transcription initiation site prediction and gene expression data classification. This paper will discuss the principles of SVMs and the applications of SVMs to the analysis of biological data, mainly protein and DNA sequences.

Algorithms↗
PubMed2003

Intelligent machines in the twenty-first century: foundations of inference and inquiry.

The last century saw the application of Boolean algebra to the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines, in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. Recent advances in our understanding of the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we recently identified the algebra of questions as the free distributive algebra, which will now allow us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper, we examine the foundations of inference and inquiry. We begin with a history of inferential reasoning, highlighting key concepts that have led to the automation of inference in modern machine-learning systems. We then discuss the foundations of inference in more detail using a modern viewpoint that relies on the mathematics of partially ordered sets and the scaffolding of lattice theory. This new viewpoint allows us to develop the logic of inquiry and introduce a measure describing the relevance of a proposed question to an unresolved issue. Last, we will demonstrate the automation of inference, and discuss how this new logic of inquiry will enable intelligent machines to ask questions. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them not only to make inferences from data, but also to decide which question to ask, which experiment to perform, or which measurement to take given what they have learned and what they are designed to understand.

Artificial Intelligence↗
PubMed2005

Toward the neurocomputer: image processing and pattern recognition with neuronal cultures.

Information processing in the nervous system is based on parallel computation, adaptation and learning. These features cannot be easily implemented on conventional silicon devices. In order to obtain a better insight of how neurons process information, we have explored the possibility of using biological neurons as parallel and adaptable computing elements for image processing and pattern recognition. Commercially available multielectrode arrays (MEAs) were used to record and stimulate the electrical activity from neuronal cultures. By mapping digital images, i.e., arrays of pixels, into the stimulation of neuronal cultures, a low and bandpass filtering of images could be quickly and easily obtained. Responses to specific spatial patterns of stimulation were potentiated by an appropriate training (tetanization). Learning allowed pattern recognition and extraction of spatial features in processed images. Therefore, neurocomputers, (i.e., hybrid devices containing man-made elements and natural neurons) seem feasible and may become a new generation of computing devices, to be developed by a synergy of Neuroscience and Material Science.

Animals↗
PubMed2004

Multimodal and ubiquitous computing systems: supporting independent-living older users.

We document the rationale and design of a multimodal interface to a pervasive/ubiquitous computing system that supports independent living by older people in their own homes. The Millennium Home system involves fitting a resident's home with sensors--these sensors can be used to trigger sequences of interaction with the resident to warn them about dangerous events, or to check if they need external help. We draw lessons from the design process and conclude the paper with implications for the design of multimodal interfaces to ubiquitous systems developed for the elderly and in healthcare, as well as for more general ubiquitous computing applications.

Activities of Daily Living↗
PubMed2004

The smart house for older persons and persons with physical disabilities: structure, technology arrangements, and perspectives.

Smart houses are considered a good alternative for the independent life of older persons and persons with disabilities. Numerous intelligent devices, embedded into the home environment, can provide the resident with both movement assistance and 24-h health monitoring. Modern home-installed systems tend to be not only physically versatile in functionality but also emotionally human-friendly, i.e., they may be able to perform their functions without disturbing the user and without causing him/her any pain, inconvenience, or movement restriction, instead possibly providing him/her with comfort and pleasure. Through an extensive survey, this paper analyzes the building blocks of smart houses, with particular attention paid to the health monitoring subsystem as an important component, by addressing the basic requirements of various sensors implemented from both research and clinical perspectives. The paper will then discuss some important issues of the future development of an intelligent residential space with a human-friendly health monitoring functional system.

Activities of Daily Living↗
PubMed2001

EthoVision: a versatile video tracking system for automation of behavioral experiments.

The need for automating behavioral observations and the evolution of systems developed for that purpose is outlined. Video tracking systems enable researchers to study behavior in a reliable and consistent way and over longer time periods than if they were using manual recording. To overcome limitations of currently available systems, we have designed EthoVision, an integrated system for automatic recording of activity, movement, and interactions of animals. The EthoVision software is presented, highlighting some key features that separate EthoVision from other systems: easy file management, independent variable definition, flexible arena and zone design, several methods of data acquisition allowing identification and tracking of multiple animals in multiple arenas, and tools for visualization of the tracks and calculation of a range of analysis parameters. A review of studies using EthoVision is presented, demonstrating the system's use in a wide variety of applications. Possible future directions for development are discussed.

Animals↗
PubMedDate not supplied

Unenhanced spiral CT for evaluating acute appendicitis in daily routine. A prospective study.

BACKGROUND/AIMS: The purpose of this study was to define in a routine setting the role of spiral computed tomography in patients with suspected acute appendicitis and to determine the effect of computed tomography on the treatment of such patients. METHODOLOGY: Appendiceal computed tomography was performed in 120 consecutive patients with acute appendicitis in the differential diagnosis, whose clinical findings were insufficient to perform surgery or to discharge from the hospital. Each scan was obtained in a single breath hold from the lower abdomen to the upper pelvis using a 5-mm collimation and a pitch of 1.6. Computed tomography results were correlated with surgical and pathologic findings at appendectomy or clinical follow-up. RESULTS: Eighty-eight of the 93 patients with acute appendicitis were correctly diagnosed by computed tomography, 24 of the 27 patients without acute appendicitis were correctly diagnosed by computed tomography (95% sensitivity, 89% specificity). Computed tomography signs of acute appendicitis included fat stranding (100%), enlarged appendix (> 6 mm) (97%), adenopathy (63%), appendicoliths (43%), abscess (10%), and phlegmon (5%). CONCLUSIONS: The use of spiral computed tomography in patients with equivocal clinical presentation suspected of having acute appendicitis led to a significant improvement in the preoperative diagnosis and a lower negative appendectomy rate. Appendiceal computed tomography is an accurate technique even if performed in the daily routine of scanning.

Acute Disease↗