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At least 991 records · Page 55Linked to original sources

Designing the design phase of critical care devices: a cognitive approach.

In this study, we show how medical devices used for patient care can be made safer if various cognitive factors involved in patient management are taken into consideration during the design phase. The objective of this paper is to describe a methodology for obtaining insights into patient safety features--derived from investigations of institutional decision making--that could be incorporated into medical devices by their designers. The design cycle of a product, be it a medical device, software, or any kind of equipment, is similar in concept, and course. Through a series of steps we obtained information related to medical errors and patient safety. These were then utilized to customize the generic device design cycle in ways that would improve the production of critical care devices. First, we provided individuals with different levels of expertise in the clinical, administrative, and engineering domains of a large hospital setting with hypothetical clinical scenarios, each of which described a medical error event involving health professionals and medical devices. Then, we asked our subjects to "think-aloud" as they read through each scenario. Using a set of questions as probes, we then asked our subjects to identify key errors and attribute them to various players. We recorded and transcribed the responses and conducted a cognitive task analysis of each scenario to identify different entities as "constant," "partially modifiable," or "modifiable." We compared our subjects' responses to the results of the task analysis and then mapped them to the modifiable entities. Lastly, we coded the relationships of these entities to the errors in medical devices. We propose that the incorporation of these modifiable entities into the device design cycle could improve the device end product for better patient safety management.

Cognitive Science↗

KDE Bioscience: platform for bioinformatics analysis workflows.

Bioinformatics is a dynamic research area in which a large number of algorithms and programs have been developed rapidly and independently without much consideration so far of the need for standardization. The lack of such common standards combined with unfriendly interfaces make it difficult for biologists to learn how to use these tools and to translate the data formats from one to another. Consequently, the construction of an integrative bioinformatics platform to facilitate biologists' research is an urgent and challenging task. KDE Bioscience is a java-based software platform that collects a variety of bioinformatics tools and provides a workflow mechanism to integrate them. Nucleotide and protein sequences from local flat files, web sites, and relational databases can be entered, annotated, and aligned. Several home-made or 3rd-party viewers are built-in to provide visualization of annotations or alignments. KDE Bioscience can also be deployed in client-server mode where simultaneous execution of the same workflow is supported for multiple users. Moreover, workflows can be published as web pages that can be executed from a web browser. The power of KDE Bioscience comes from the integrated algorithms and data sources. With its generic workflow mechanism other novel calculations and simulations can be integrated to augment the current sequence analysis functions. Because of this flexible and extensible architecture, KDE Bioscience makes an ideal integrated informatics environment for future bioinformatics or systems biology research.

Biological Science Disciplines↗

Models of the subthalamic nucleus. The importance of intranuclear connectivity.

A coherent set of models is presented that provide novel and testable predictions about the functional role of the subthalamic nucleus (STN) in the basal ganglia. The STN is emerging as an important target for novel therapeutic strategies for the alleviation of Parkinsonian type symptoms [Lancet 345 (1995) 91; Science 249 (1990) 1436]. Computational and mathematical models based on the properties of the STN and its interactions are reviewed. These models focus on core anatomical and physiological data that span many levels. By assessing models of anatomy, dynamic network models, and a detailed model of a recent pharmacological experiment, we can expose the primary modes of STN function and highlight their underlying properties. We show that the presence of functional interactions between STN projection neurons is critical in defining its behaviour and how it interacts with other basal ganglia nuclei. Pulses or switch-like activity patterns emerge in the models as a consequence of these local interactions. Furthermore, the models demonstrate that this behaviour can break down under abnormal conditions resulting in low frequency bursting oscillations. Such oscillations may play a role in symptoms of Parkinson's disease.

Action Potentials↗

NanoSystems biology.

Systems biology is an approach in which the digital information of the genome, acted upon by environmental cues, generates the many molecular signatures of gene and protein expression, as well as other, more phenomenological experimental observations. These data may be integrated together to form a testable hypothesis of how a biological organism functions as a system. The central components of systems biology are genetically programmed networks (circuits) within cells and networks of cells. These components establish the organization and function of individual cells and tissues in response to environmental signals such as cell-to-cell communication within organ systems and whole organisms. Within this context, disease is considered as a genetic or environmental reprogramming of cells to gain or lose specific functions that are characteristics of disease. This paper is a combination of three tutorials with an outlined series of technologies, including microfluidics, nanotechnologies, and molecular imaging methods, and we describe how their development should be driven by the needs of systems biology. We also discuss how these technologies can enable a systems biology approach through a pathway from single cells to mouse models of disease and finally to patients. Within this technology base are approaches to develop, use and test molecules as probes that target proteins, DNA and mRNA to test systems biology models, as well as provide molecular diagnostics and molecular therapeutics within a systems biology framework.

Animals↗

The evolution of imaging in advanced prostate cancer.

Medical advances will be driven by the enhancement of imaging for diagnosis, refinement of treatment, and evaluation of treatment efficacy. The convergence of technology in materials science, biology, and the computer industry has greatly advanced diagnostic imaging. Precision in control of the spatial and temporal properties of light and its heterogeneous scattering properties have extended our capability for imaging. Refinements in radioimmunoscintigraphy for image acquisition, fusion of images, and outcome data now suggest use for image-guided therapy. Novel MRI agents appear to provide significant imaging capabilities to detect malignant lymph nodes. Future applications of optical coherence tomography, electron paramagnetic resonance imaging, nanotechnology, molecular imaging, and hyperspectral spectroscopy promise further refinements to image tissues for diagnosis.

Diagnostic Imaging↗

The application of "CrimeLite" to examination of computer components "in situ".

The authors consider the problem of identifying potential fingerprints and other marks in a computer system, having regard for the damage which conventional print enhancement techniques may cause. They evaluate a non-invasive method of mark location and recommend a new procedure for the handling of digital evidence sources which may contain "conventional" evidence.

Computer Systems↗

Text-based knowledge discovery: search and mining of life-sciences documents.

Text literature is playing an increasingly important role in biomedical discovery. The challenge is to manage the increasing volume, complexity and specialization of knowledge expressed in this literature. Although information retrieval or text searching is useful, it is not sufficient to find specific facts and relations. Information extraction methods are evolving to extract automatically specific, fine-grained terms corresponding to the names of entities referred to in the text, and the relationships that connect these terms. Information extraction is, in turn, a means to an end, and knowledge discovery methods are evolving for the discovery of still more-complex structures and connections among facts. These methods provide an interpretive context for understanding the meaning of biological data.

Biological Science Disciplines↗

Web services in the life sciences.

Web services provide a standard way of publishing applications and data sources over the internet, enabling mass dissemination of knowledge. In the life sciences, the web-service approach is seen as being a road to standardizing the multitude of tools available from different providers. In this article, we present an overview of the technology (focusing on life-science applications), we list the currently available service providers and we discuss advanced issues raised by the concept.

Biological Science Disciplines↗

Simplicity: a unifying principle in cognitive science?

Much of perception, learning and high-level cognition involves finding patterns in data. But there are always infinitely many patterns compatible with any finite amount of data. How does the cognitive system choose 'sensible' patterns? A long tradition in epistemology, philosophy of science, and mathematical and computational theories of learning argues that patterns 'should' be chosen according to how simply they explain the data. This article reviews research exploring the idea that simplicity drives a wide range of cognitive processes. We outline mathematical theory, computational results and empirical data that underpin this viewpoint.

Journal Article↗

Changing perspectives of apheresis in India in the twentieth century.

Globally, the last century (20th) has seen many changes in terms of amazing advancements and applications of modern science, medicine, biotechnology and computers. One of the dramatic outcomes of such great inventions and discoveries was that the medical profession got the wonderful tool of immunomodulation and haemapheresis which has changed the outlook of the entire spectrum of immune complex disorders both in terms of the great success in treatment and the rehabilitation from so-called incurable diseases. Additionally this has resulted in a better quality of life and lower morbidity and mortality. Organ transplants have become a reality and immunomodulation plays a pivotal role in their success. India also has tasted this sweet recipe of modern medicine and has imbibed it in its medical culture. India is not only famous for the Taj Mahal and Hawa Mahal (Agra and Jaipur) but also for its brain (of brain drain/otherwise) and betz cells which have brought glories and laurels in the field of medicine, mathematics, engineering, literature, physics and computers, etc. to the native countries and India equally. Apheresis has now invaded the Indian scenario also and there is a growing interest, demand and application for it in the clinical field. But, being a unique country, the problems encountered are also unique. This paper deals with an overview of the changing perspectives of apheresis in India in the 20th century.

Blood Component Removal↗

Orthodontic undergraduate education: developments in a modern curriculum.

This paper explores some modern concepts of teaching and learning, including cognitive theory, the zone of proximal development, constructivism, andragogy and learning styles and describes how they have informed the development of an undergraduate orthodontic curriculum. The changes described include student-centred learning, guided self-learning, and the incorporation of problem-based learning concepts. The details of the problem-based learning programme are described together with results of student feedback on the change in teaching and learning style.

Adult↗

Addressing the problems with life-science databases for traditional uses and systems biology.

A prerequisite to systems biology is the integration of heterogeneous experimental data, which are stored in numerous life-science databases. However, a wide range of obstacles that relate to access, handling and integration impede the efficient use of the contents of these databases. Addressing these issues will not only be essential for progress in systems biology, it will also be crucial for sustaining the more traditional uses of life-science databases.

Animals↗

Optical and structural modeling of disclination lattices in carbonaceous mesophases.

An integrated microstructural and optical model for carbonaceous mesophases is developed and used to explain the principles that govern the formation and stability of experimentally observed disclination lattices. The model is able to capture the orientation features of disclination lattices, including the type and location of disclination lines, and the orientation field in the mesophase matrix. The optical model based on reflection polarized optical microscopy is able to replicate all the details observed in actual observations. The typical brush figures have the proper distribution, orientation, and intensity. The computational predictions offer science-based routes to create and control desirable material architectures based on carbonaceous mesophase-carbon fiber composites.

Journal Article↗

Modularity and community structure in networks.

Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as "modularity" over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.

Journal Article↗