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At least 667 records · Page 37Linked to original sources
PubMed2006

Laser imaging and computer-aided design and computer-aided manufacture in prosthetics and orthotics.

Although Hanger Orthopedic Group, Inc., has been developing clinical protocols for its INSIGNIA scanner for more than 2 years, there are many applications that are currently in development and will be released over the next 2-year period after this publication. It is the goal of Hanger Orthopedic Group, Inc., to replace all plaster casting procedures with the laser scan and move toward a paperless environment where all images and documents are passed through its virtual network. INSIGNIA currently has five major production centers throughout the United States, which support more than 600 INSIGNIA certified clinicians. These clinicians staff more than 600 clinics in North America, all under the Hanger company name. The central fabrication service and the central design center processes hundreds of shapes per day (Fig. 27). So that any clinician in the field can use the expertise of the central designers and central fabricators to help with overflow or problems they might be having, the network that exists within Hanger is tied together and enhanced by INSIGNIA. Through virtual modification and centralization of these services, each patient receives the virtual collaboration of several clinicians with a total of years of experience. INSIGNIA has enhanced the patient experience. The enhancement is not only in removing the plaster from the process, but also in exposing each patient to the team of prosthetic experts working collaboratively behind the scenes. The rehabilitation industry continues to be bombarded with compliance paperwork and justifications. The INSIGNIA scan and resulting measurement reports give inherent strength to justifications based on volume change, surgical revisions, or tissue change. The files are kept in a data warehouse where they are vaulted and preserved presumably forever. Also, any of the shape graphics or measurement instruments can be printed into a discrete report that can become part of the patient's permanent record. Many physicians receive update letters from their orthotic and prosthetic clinician with a status update before and after treatment of their patient. This update includes a descriptive narrative, a printout of the pertinent metrics, a printout of the scan graphic, and often a digital image of the patient wearing the device (Fig. 28). The network is HIPAA compliant, and all private health information is held in tight security. If a practitioner does not have a HIPAA agreement in place with Hanger Orthopedic Group, Inc., and would like one, or ifa practitioner would like to have an INSIGNIA representative call or visit with more information, the practitioner is encouraged to call 1-800-4-HANGER and request an INSIGNIA in-service or visit INSIGNIA on the web at www.hanger.com.

Adult↗
PubMedDate not supplied

[Application of neural networks in occupational medicine].

The medical literature offers today many contributions in which neural networks have been used. The introduction of these tools as diagnostic aid appears very interesting also into various sectors of research in the occupational field. The author proceeds to a schematic description of the functioning of a neural network, describing an applied example. It is therefore estimated the feasible advantages which result from the use in the research of neural networks. Finally a possible fields of use of the neural networks in occupational medicine is highlighted, from the detection of lung nodules in digital chest radiographs to the detection of peripheral vascular disease from upper limb pulse waveforms, from the low back disorders due to workplace design to the diagnosis of occupational asthma.

Forecasting↗
PubMed1990

[Long-term experience with a PACS subsystem].

Our experiences with a PACS-Subsystem have shown, that it would be more usefull and less expensive, first to install digital archiving systems in single areas. After a certain time of errorfree working the subsstems should be integrated into a superior information system. Fast data networks and userfriendly viewing stations are a basic requirement. Common standards of archiving, independent of the manufacturer, should be considered.

Angiography, Digital Subtraction↗
PubMed1999

Simulating prosopagnosia through a lesion of lateral connections in a feed-forward neural network.

We show that particular features of prosopagnosic impairment can be simulated by a connectionist model trained with an unsupervised learning procedure. In particular we describe a Kohonen's neural network which is able to correctly recognize and categorize a series of digitized pictures of faces when learning is characterized by certain parameter values, but which shows a prosopagnosic behavior when lateral connections are lesioned. We discuss the relationship between this result and some neurophysiological hypotheses about prosopagnosia.

Computer Simulation↗
PubMed1997

Network Synthesis through Data-Driven Growth and Decay.

AN ALGORITHM FOR ADDITION AND DELETION (ADDEL) OF RESOURCES DURING LEARNING IS DEVELOPED TO ACHIEVE TWO GOALS: (1) to find feed-forward multilayer networks that are as small as possible, (2) to find an appropriate structure for such small networks. These goals are accomplished by operating alternately between an adding phase and a deleting phase while learning the given input-output associations. The adding phase develops a crude structure by filling in resources (connections, units and layers) at a virtual multilayer network with a maximum of L possible layers. The deleting phase then removes any unnecessary connections to obtain a refined structure. The additions and deletions are done based on a sensitivity measure and a corresponding probability rule so that only the synapses which are most effective in reducing the output error are preserved. A generalization error estimated from a validation set is used to control the alternation between the two learning phases and the termination of learning. Simulations, including handwritten digit recognition, demonstrate that the algorithm is effective in finding an appropriate network structure for a small network which can generalize well. The algorithm is used to investigate when the size of a network is important for generalization. Copyright 1997 Elsevier Science Ltd.

Journal Article↗
PubMed2003

Diabetes Patient Tracker, a personal digital assistant-based diabetes management system for primary care practices in Oklahoma.

It has been demonstrated that electronic patient registries combined with a clinical decision support system have a significant positive impact on the documentation and delivery of services provided by health care professionals. While implementation of available commercial systems has not always been proven effective in a number of primary care practices, development and implementation of such a system in a practice-based research network might enhance successful implementation. Physicians in our practice-based research network (Oklahoma Physicians Resource/Research Network) initiated a project that aimed at designing, testing, and implementing a personal digital assistant-based diabetes management system. We utilized the "best practice" approach to determine the principles on which the application must operate. System development and beta testing were also accomplished based on the direct feedback of user clinicians. Practice Enhancement Assistants (PEAs) were available in the practices for assistance with implementation. Implementation of the Diabetes Patient Tracker (DPT) resulted in a significant improvement (p<0.05) in nine of 10 diabetic quality of care measures compared with pre-intervention levels in 20 primary care practices. Regular PEA visits similarly increased the number of foot exams and retinal exams performed in the last year (p=0.03 and 0.02, respectively). DPT is a low-cost, feasible, easily implementable, and very effective paper-less tool that significantly improves patient care and documentation in primary care practices.

Computer-Assisted Instruction↗
PubMed2007

Coding with spike shapes and graded potentials in cortical networks.

In cortical neurones, analogue dendritic potentials are thought to be encoded into patterns of digital spikes. According to this view, neuronal codes and computations are based on the temporal patterns of spikes: spike times, bursts or spike rates. Recently, we proposed an 'action potential waveform code' for cortical pyramidal neurones in which the spike shape carries information. Broader somatic action potentials are reliably produced in response to higher conductance input, allowing for four times more information transfer than spike times alone. This information is preserved during synaptic integration in a single neurone, as back-propagating action potentials of diverse shapes differentially shunt incoming postsynaptic potentials and so participate in the next round of spike generation. An open question has been whether the information in action potential waveforms can also survive axonal conduction and directly influence synaptic transmission to neighbouring neurones. Several new findings have now brought new light to this subject, showing cortical information processing that transcends the classical models.

Action Potentials↗
PubMed2002

The digital microscopy classroom.

This paper describes the implementation and functionality of a base-band network for the remote control of scientific instruments, in particular scanning and transmission electron microscopes. The base-band network is a hard-wired connection between keyboard and pointing devices from the remote computers to the CPU of the instrument computer; the video signal is then routed back to the remote user and to a high resolution projection system. The system is independent of software and hardware platform, and is highly reliable.

Computer Simulation↗
PubMed2005

[Digital teaching archive. Concept, implementation, and experiences in a university setting].

Film-based teaching files require a substantial investment in human, logistic, and financial resources. The combination of computer and network technology facilitates the workflow integration of distributing radiologic teaching cases within an institution (intranet) or via the World Wide Web (Internet). A digital teaching file (DTF) should include the following basic functions: image import from different sources and of different formats, editing of imported images, uniform case classification, quality control (peer review), a controlled access of different user groups (in-house and external), and an efficient retrieval strategy. The portable network graphics image format (PNG) is especially suitable for DTFs because of several features: pixel support, 2D-interlacing, gamma correction, and lossless compression. The American College of Radiology (ACR) "Index for Radiological Diagnoses" is hierarchically organized and thus an ideal classification system for a DTF. Computer-based training (CBT) in radiology is described in numerous publications, from supplementing traditional learning methods to certified education via the Internet. Attractiveness of a CBT application can be increased by integration of graphical and interactive elements but makes workflow integration of daily case input more difficult. Our DTF was built with established Internet instruments and integrated into a heterogeneous PACS/RIS environment. It facilitates a quick transfer (DICOM_Send) of selected images at the time of interpretation to the DTF and access to the DTF application at any time anywhere within the university hospital intranet employing a standard web browser. A DTF is a small but important building block in an institutional strategy of knowledge management.

Computer-Assisted Instruction↗
PubMed2003

Distributions of gamma-aminobutyric acid immunoreactive and acetylcholinesterase-containing cells in the primary olfactory system in the terrestrial slug Limax marginatus.

The tentacular ganglion, the primary olfactory system of terrestrial slugs, exhibits spontaneous oscillations with a spatial coherence. The digit-like extensions (digits) of the tentacular ganglion presumably house the cell bodies of the neurons underlying the oscillations. The present study was designed to identify the anatomical and physiological determinants of these oscillations with a special focus on whether the neurons located in the digits contribute to the coherent oscillations. We recorded field potentials from the spatially separated sites in the digits in the terrestrial slug Limax marginatus. We also simultaneously recorded tentacular nerve to monitor the coherent oscillations. The spatially separated regions in the digits oscillated at the same frequency as the tentacular nerve, indicating a single coherent activity. To study the neural networks underlying the coherent oscillations, we examined the distributions of acetylcholinesterase (AChE)-containing and gamma-aminobutyric acid immunoreactive (GABA-ir) neurons. AChE-containing and GABA-ir fibers were found to connect the neurons in a branch of the digits with those in other branches. We also used a vital staining technique with 1,1'-didodecyl-3,3,3',3'-tetramethylindocarbocyanine perchlorate to examine the projections of neurons in the digits. Large stained cells were detected in many branches of the digits after placing the dye on one of the cell masses located in right and left sides of the tentacular ganglion. They were detected in the cell masses and in many branches of the digits after placing the dye on a branch of the digits. Our results showed that the slug primary olfactory system has highly interconnected neural networks.

Acetylcholinesterase↗
PubMed1990

Teleradiology: an assessment.

A teleradiology system acquires radiographic images at one location and transmits them to one or more remote sites, where they are displayed and/or converted to hard copy. These systems often employ wide area networks. Their goal is to provide improved radiologic services at all sites on the network. Experience in the use of teleradiology systems has demonstrated the need for a laser film digitizer, an optical disk, and a high-quality display and/or laser film printer at each site. Single-site hardware purchase costs average $196,000, plus an additional 20% for yearly network services. Hardware purchased for a consultation or central referral facility approximates $344,000.

Computer Communication Networks↗
PubMed1999

Analog neural nets with gaussian or other common noise distribution cannot recognize arbitrary regular languages.

We consider recurrent analog neural nets where the output of each gate is subject to gaussian noise or any other common noise distribution that is nonzero on a sufficiently large part of the state-space. We show that many regular languages cannot be recognized by networks of this type, and we give a precise characterization of languages that can be recognized. This result implies severe constraints on possibilities for constructing recurrent analog neural nets that are robust against realistic types of analog noise. On the other hand, we present a method for constructing feedforward analog neural nets that are robust with regard to analog noise of this type.

Analog-Digital Conversion↗
PubMed1988

Arteriovenous distribution of transit times in cremaster muscle of the rat.

Video digitization was applied to determine the arteriovenous transit time (TT) of blood flow between functionally paired arterioles and venules in cremaster muscle (rat). After a bolus injection of cell-free dye (FITC-Dextran) into a contralateral femoral artery, intensity-time curves (ITCs) of the fluorescent emissions were recorded in successive network divisions. TTs were calculated by cross-correlation of ITCs acquired from the video images digitized at rates of 5-10 frames/sec for up to 10 arteriole-venule (AV) pairs per video field whose position in the network was characterized in terms of centrifugal order of branching. Mean TT for first-order AV pairs averaged 3.74 +/- 1.62 (SD) sec and decreased significantly to 0.76 +/- 0.95 sec in the fifth-order pairs, with 75% of this reduction occurring between the first- and third-order pairs. A near threefold increase in coefficient of variation from first to fifth orders evidenced a marked increase in the spatial heterogeneity of TT at the level of the true capillaries. Comparison of TT with distance along the arterial tree from the tissue hilus revealed consistently stronger correlations than with AV order. These trends suggest that TT may be a superior indicator of the functional deployment of microvessels compared to branching order.

Animals↗
PubMed1996

Using artificial bat sonar neural networks for complex pattern recognition: recognizing faces and the speed of a moving target.

Two sets of studies examined the viability of using bat-like sonar input for artificial neural networks in complex pattern recognition tasks. In the first set of studies, a sonar neural network was required to perform two face recognition tasks. In the first task, the network was trained to recognize different faces regardless of facial expressions. Following training, the network was tested on its ability to generalize and correctly recognize faces using echoes of novel facial expressions that were not included in the training set. The neural network was able to recognize novel echoes of faces almost perfectly (above 96% accuracy) when it was required to recognize up to five faces. In the second face recognition task, a sonar neural network was trained to recognize the sex of 16 faces (eight males and eight females). After training, the network was able to correctly recognize novel echoes of those faces as 'male' or as 'female' faces with accuracy levels of 88%. However, the network was not able to recognize novel faces as 'male' or 'female' faces. In the second set of studies, a sonar neural network was required to learn to recognize the speed of a target that was moving towards the viewer. During training, the target was presented in a variety of orientations, and the network's performance was evaluated when the target was presented in novel orientations that were not included in the training set. The different orientations dramatically affected the amplitude and the frequency composition of the echoes. The neural network was able to learn and recognize the speed of a moving target, and to generalize to new orientations of the target. However, the network was not able to generalize to new speeds that were not included in the training set. The potential and limitations of using bat-like sonar as input for artifical neural networks are discussed.

Adult↗