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PubMed1987

On the use of statistics for representing the knowledge acquired from experts in a medical consulting system.

For making medical consulting systems, it is important and significant to select and devise the method for representing the knowledge acquired from professional experts. As quantities of data required for consultation are increasing according to the progress of medical science, we have to introduce some new kinds of statistics into a medical consultation system. From another point of view, since the process of diagnosis of experts is considered to be a kind of effective model for compressing (or condensing) data quantitatively and qualitatively, we discuss the use of statistics for representing the knowledge acquired from experts from the standpoint of data compression.

Adult↗

PubMedDate not supplied

A feature extraction unsupervised neural network for an environmental data set.

Environmental data sets are characterized by a huge amount of heterogeneous data from external fields. As the number of measured points grows, a strategy is needed to select and efficiently analyze the useful information from the whole data set. One efficient way of obtaining the validation-compression of data sets is the adoption of a restricted set of features that describe, with an assigned accuracy a subset of the whole data set. One characteristic feature of the environmental data is time dependency: in the medium and long term they are not stationary data sets. The aim of this work is to propose a feature extraction technique based on a new model of an unsupervised neural network suitable to analyze this kind of data. The paper reports the results obtained utilizing the above extraction and analysis procedure on a real data set on chemical pollutants. It is shown that the proposed neural network is able to identify correctly human and/or meteorological effects in the environmental data set.

Databases, Factual↗

PubMed2003

Myoelectric signal compression using zero-trees of wavelet coefficients.

Recent progress in the diagnostic use of the myoelectric signal for neuromuscular diseases, coupled with increasing interests in telemedicine applications, mandate the need for an effective compression technique. The efficacy of the embedded zero-tree wavelet compression algorithm is examined with respect to some important analysis parameters (the length of the analysis segment and wavelet type) and measurement conditions (muscle type and contraction type). It is shown that compression performance improves with segment length, and that good choices of wavelet type include the Meyer wavelet and the fifth order biorthogonal wavelet. The effects of different muscle sites and contraction types on compression performance are less conclusive.A comparison of a number of lossy compression techniques has revealed that the EZW algorithm exhibits superior performance to a hard thresholding wavelet approach, but falls short of adaptive differential pulse code modulation. The bit prioritization capability of the EZW algorithm allows one to specify the compression factor online, making it an appealing technique for streaming data applications, as often encountered in telemedicine.

Adult↗

PubMed1998

The function of sensory nerve fibers in lumbar radiculopathy. Use of quantitative sensory testing in the exploration of different populations of nerve fibers and dermatomes.

STUDY DESIGN: The function of sensory nerve fibers in patients with lumbar radiculopathy and in control individuals was evaluated using quantitative sensory testing. OBJECTIVES: To investigate the effect of lumbar nerve root compression on different populations of nerve fibers and to explore the function of sensory nerve fibers in neighboring nerve roots not involved in the mechanical compression. BACKGROUND DATA: Results from experimental and clinical studies indicate that chronic compression of lumbar nerve roots affects the large myelinated nerve fibers. The majority of nerve fibers involved in the sensation of pain, however, are small afferent nerve fibers. It is therefore of interest to study the effect of compression on large and small sensory afferent channels. Several authors have elucidated the biochemical interaction between disc tissue and nerve roots. Chemical substances in the epidural space can reach the nerve fibers in nerve roots at the same or neighboring lumbar segments. In this way, fibers not involved in the mechanical compression may be affected. METHODS: The small nerve fibers were studied using tests for thermal thresholds (thermotest), and the large myelinated fibers were studied by vibrametry. Forty-two patients were investigated in the symptomatic and the asymptomatic leg, and the results were compared with those of 21 healthy individuals. RESULTS: The thresholds of cold, warmth, and vibration were significantly increased in the dermatome of the compressed nerve root, indicating that large and small sensory nerve fibers were affected. Further, the thresholds were significantly increased in the neighboring dermatomes in the symptomatic and the asymptomatic leg. CONCLUSION: Large and small sensory afferent nerve fibers are affected in lumbar radiculopathy. The increase in sensation thresholds in the ipsilateral neighboring dermatome and in the dermatomes in the asymptomatic leg indicates that adjacent nerve roots are involved in the pathophysiology of sciatica in patients with lumbar disc herniation.

Adult↗

PubMed1996

Factors affecting performance of PACS.

We experimentally constructed a personal-computer-based Picture Archiving and Communication System (PACS) for color images of dermatology clinics. This system should especially satisfy such a demand as to be able to retrieve an image within a few seconds from the database residing in a remote server. Our two objectives in the experiment were: To examine how much time was consumed in each part of PACS while it does a series of jobs, from the requesting of an image to its display on the screen of the workstation of the user. The other objective was to see if a personal-computer-based PACS could satisfy our criteria. Total retrieving time, data reading time, data transporting time and image displaying time were measured. Total retrieving time can be divided into three procedures: Data reading time, data transporting time, image displaying time. Data reading time was about 0.6 second for reading an image with the size of 1 mega bytes (MB). Data reading time and the size of data were linearly correlated. Data transporting time was about 11 seconds for transporting an image with the size of 1 MB through EtherTalk, and 66 seconds through LocalTalk. Data transporting time and the size of the data were also linearly correlated. Data reading time and data transporting time was able to be reduced largely by compression technique. However, smaller data give other important effects to the network system besides reducing the time of data reading, data transporting and data displaying. Most Local Area using image Network (LAN) systems, such as EtherTalk, adopt Carrier Sense Multiple Access with Collision Detection (CSMA/CD) for the way of accessing to other computer. In CSMA/CD, transporting performance suddenly declines if the congestion of signal in a network gets beyond a critical level. This situation fatally impairs the performance of a network. We concluded that data compression plays an important role to improve the performances of PACS, especially those of a server and the network system. A personal-computer-based PACS with EtherTalk and an image compression/decompression hardware, e.g., CL550A chip, satisfies our criteria.

Dermatology↗

PubMed2005

[Lossless ECG compression algorithm with anti- electromagnetic interference].

Based on the study of ECG signal features, a new lossless ECG compression algorithm is put forward here. We apply second-order difference operation with anti- electromagnetic interference to original ECG signals and then, compress the result by the escape-based coding model. In spite of serious 50Hz-interference, the algorithm is still capable of obtaining a high compression ratio.

Algorithms↗

PubMed2005

SIMPLISMA and ALS applied to two-way nonlinear wavelet compressed ion mobility spectra of chemical warfare agent simulants.

Ion mobility spectrometry is a rapid scanning measurement method for which compression methods that facilitate the handling of large collections of data are beneficial. Peak distortion in reconstructed ion mobility spectra from linear wavelet compression is problematic in that artifact peaks may cause false positive alarms. Peak shifting also may cause false alarms if target peaks shift out of or interfering peaks shift into detection windows. Nonlinear wavelet compression (NLWC) preserves peak shape and can lessen the degree of distortion, shifting, and artifact peaks in the reconstructed spectra. NLWC was applied to achieve high compression and fidelity in the reconstructed spectra. Another benefit is that NLWC improves signal-to-noise ratios and thus the models built from compressed data are improved. By compressing both the drift time order and the spectrum acquisition order, greater compressions maybe achieved. A two-way nonlinear wavelet compression method that incorporates alternating least squares (2W-NLWC-ALS) algorithm was devised by applying ALS to partially reconstructed wavelet coefficients generated from two-way NLWC. The number of components in a data set can be determined automatically using ASIMPLISMA. The smaller ALS models are saved as the final compressed data and can be used to reconstruct the entire data set efficiently without maintaining the compressed wavelet coefficient matrix of the original data set. The 2W-NLWC-ALS algorithm provides greater compression ratios compared to regular wavelet compression and interpretable models. Using this method, large volumes of data can be acquired and easily evaluated through a simple compressed model. A compression ratio of 510 ppm, root-mean-square error (E(RMS)) of 6.3 mV (full-scale signal is usually 1 V or larger), and relative root-mean-square error (RE(RMS)) of 1.62% were achieved for data sets collected by CAM. A compression ratio of 46 ppm, E(RMS) of 9.2 mV, and RE(RMS) of 0.42% were achieved for data sets collected with an ITEMISER instrument. The 2W-NLWC-ALS algorithm is an efficient compression method that provides the benefits of a simple model.

Algorithms↗

PubMed2003

Coupling proton transfer reaction-mass spectrometry with linear discriminant analysis: a case study.

Proton transfer reaction-mass spectrometry (PTR-MS) measurements on single intact strawberry fruits were combined with an appropriate data analysis based on compression of spectrometric data followed by class modeling. In a first experiment 8 of 9 different strawberry varieties measured on the third to fourth day after harvest could be successfully distinguished by linear discriminant analysis (LDA) on PTR-MS spectra compressed by discriminant partial least squares (dPLS). In a second experiment two varieties were investigated as to whether different growing conditions (open field, tunnel), location, and/or harvesting time can affect the proposed classification method. Internal cross-validation gives 27 successes of 28 tests for the 9 varieties experiment and 100% for the 2 clones experiment (30 samples). For one clone, present in both experiments, the models developed for one experiment were successfully tested with the homogeneous independent data of the other with success rates of 100% (3 of 3) and 93% (14 of 15), respectively. This is an indication that the proposed combination of PTR-MS with discriminant analysis and class modeling provides a new and valuable tool for product classification in agroindustrial applications.

Discriminant Analysis↗

PubMed1951