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At least 163 records · Page 9Linked to original sources
PubMed1990

Non-linear statistical technique applied to data from baboon articular cartilage.

Pattern recognition software was developed and applied together with statistical techniques to articular cartilage data from the knee joint of the baboon. The standard statistical method used for comparison was ANOVA which indicates linear discrimination. In addition a Karhunen-Loève expansion was performed to reduce the dimensionality of the data and provide independent uncorrelated variables. Nearest neighbour analysis, a non-linear method, when combined with bionomial probabilities gave discrimination that was not obtained by ANOVA. Use of pattern recognition and related techniques can improve and extend the analysis of biological data to include non-linear discrimination and classification.

Algorithms↗
PubMed1992

A nationwide survey of migraine in France: prevalence and clinical features in adults. GRIM.

In November 1990 a nationwide survey of migraine was conducted in France on a representative sample of residents aged 15 years and older. The diagnosis of migraine was based on the International Headache Society (IHS) classification. In a previous study, we validated a diagnostic algorithm which classifies headache sufferers as IHS migraine, "borderline" migraine, possible migraine and non-migrainous headache. The overall prevalence of migraine patients with the IHS criteria in the present study was 8.1%; another 4% were classified as "borderline" migraine, which we in fact considered as definite migraine. Age, gender and occupation were found to be risk factors for migraine. Neither frequency and duration of attacks nor length of time of disease differed with gender. Expressed intensity of attacks, however, was greater in females.

Adolescent↗
PubMed1990

Temporal feature extraction and clustering analysis of electromyographic linear envelopes in gait studies.

A technique for automatically clustering linear envelopes of the EMG during gait has been developed which uses a temporal feature representation and a maximum peak matching scheme. This new technique provides a viable way to define compact and meaningful EMG waveform features. The envelope matching is performed by dynamic programming, providing qualitatively the largest numbers of matched peaks and quantitatively a minimum distance measurement. The resulting averaged EMG profiles have low statistical variation and can serve as templates for EMG comparison and further classification.

Algorithms↗
PubMed1986

Allele and locus classification in electrophoretic population studies.

The electrophoretic separation of protein variants having slightly different mobilities is a basic tool of biochemical population genetics. In certain situations it is difficult to determine how to classify the variants as alleles of a number of genetic loci, that is, as variant subsets within each of which the Mendelian laws hold. In this article, we develop and analyze a series of algorithms for solving various versions and generalizations of this problem of optimal classification.

Alleles↗
PubMed1989

Automatic detection of gait events: a case study using inductive learning techniques.

One of the problems which occurs in the development of a control system for functional electrical stimulation of the lower limbs is to detect accurately specific events within the gait cycle. We present a method for the classification of phases of the gait cycle using the artificial intelligence technique of inductive learning. Both the terminology of inductive learning and the algorithm used for the analyses are fully explained. Given a set of examples of sensor data from the gait events that are to be detected, the inductive learning algorithm is able to produce a decision tree (or set of rules) which classify the data using a minimum number of sensors. The nature of the redundancy of the sensor set is examined by progressively removing combinations of sensors and noting the effect on both the size of the decision trees produced and their classification accuracy on 'unseen' testing data. Since the algorithm is able to calculate which sensors are more important (informative), comparisons with the intuitive appreciation of sensor importance of five researchers in the fields were made, revealing that those sensors which appear intuitively most informative may, in fact, provide the least information. Comparison results with the standard statistical classification technique of linear discriminant analysis are also presented, showing the relative simplicity of the inductively derived rules together with their good classification accuracy. In addition to the control of FES, such techniques are also applicable to automatic gait analysis and the construction of expert systems for diagnosis of gait pathologies.

Algorithms↗
PubMed1990

Echographic tissue characterization in diffuse parenchymal liver disease: correlation of image structure with histology.

Seventy livers were examined in vitro using a computerized ultrasound B-mode data acquisition and analysis system. For tissue characterization, statistical parameters from pattern recognition algorithms describing image brightness and image structure were used. Reference classification based on histopathology as well as on chemical/morphometrical analysis led to the diagnostic classes of normal, fatty liver, fibrosis/cirrhosis and fatty fibrosis/cirrhosis. Comparing the two reference methods for ultrasound tissue characterization, reclassification based on chemical/morphometrical analysis resulted in a significant increase in diagnostic accuracy. The strong correlations between statistical ultrasound image parameters and morphometrical features reflect the relevance of our statistical approach to ultrasound tissue characterization.

Fatty Liver↗
PubMed1992

Expert system design in hematology diagnosis.

A two-part study was designed to test the hypothesis that sufficient information is available from a modern hematology analyzer (the Coulter STKS) to reach a reliable intermediate conclusion which can be used as input to the next decision-making level in the design of a high-performance expert system for hematology diagnosis. In phase one, we analyzed the performance of three probabilistic systems (using Bayes' rule) which interpret STKS data: a control system which took the traditional approach of classifying cases into specific diagnoses, and two test systems which were designed to reach only an intermediate conclusion but not a final diagnosis. One of the test systems classified cases into "textbook categories" of disease and the other utilized defined diagnostic patterns. The systems were tested with 150 cases. The pattern approach ranked the correct choice first in 141 of 150 cases (94%). In phase two, we abandoned Bayes' rule, reformulated the pattern approach into a heuristic classification system, and tested its reliability on 820 cases. The algorithm of the reformulated system was able to classify all 820 cases into the same predominant pattern as a panel of three experienced laboratory hematologists.

Algorithms↗
PubMed1986

An algorithm for the management of scoliosis.

Scoliosis is a lateral and rotary deformity of the spine that is often found in children. Treatment of this deformity is based on the principle of early recognition and prevention, although surgical correction may be warranted in the case of progressive curves. There is no scientific evidence that spinal manipulative therapy (SMT) has any effect on curve progression in patients with idiopathic scoliosis; however, there is clinical evidence that SMT is a useful treatment for those patients who have an associated mechanical backache. This paper reviews the classification, natural history, pathogenesis, and clinical and radiological assessment of scoliosis. An algorithm for the management of scoliosis by chiropractors is presented, and illustrative cases from a scoliosis clinic in a university hospital are used to reinforce important clinical principles.

Adolescent↗
PubMedDate not supplied

[Empirical French criteria for psychoses. III. Algorithms and decision tree].

The present report presents the final results of an empirical investigation initiated to establish operational definitions for schizophrenia and other non-affective psychoses of classical French nosology. For each category, the authors provide diagnostic criteria and algorithms. In addition, they propose a decision tree for the differential diagnosis of psychotic features included in the French classification of mental disorders.

Affective Disorders, Psychotic↗
PubMed1990

Self-organization of associative memory and pattern classification: recurrent signal processing on topological feature maps.

We extend the neural concepts of topological feature maps towards self-organization of auto-associative memory and hierarchical pattern classification. As is well-known, topological maps for statistical data sets store information on the associated probability densities. To extract that information we introduce a recurrent dynamics of signal processing. We show that the dynamics converts a topological map into an auto-associative memory for real-valued feature vectors which is capable to perform a cluster analysis. The neural network scheme thus developed represents a generalization of non-linear matrix-type associative memories. The results naturally lead to the concept of a feature atlas and an associated scheme of self-organized, hierarchical pattern classification.

Algorithms↗
PubMed1990

Automatic computer detection of clustered calcifications in digital mammograms.

The automatic detection of clusters of calcifications in digital mammograms has been investigated using image analysis techniques. The calcifications were segmented from the background of normal breast structure in the mammogram using a local area thresholding process. This procedure also identified other breast structures and the digital image properties of all segmented objects were analysed to extract clusters of calcifications. Seventy five clinical mammograms were digitised. These were divided into training and test sets of 25 and 50 films respectively. The results for the test set of 50 complete clinical mammograms show that the computer system achieves a 25/25 true positive film classification (i.e. those containing clusters of calcifications) with false positive clusters detected in 4/50 films. There were no false negative film classifications.

Algorithms↗
PubMed1992

Case-mix groups for VA hospital-based home care.

The purpose of this study is to group hospital-based home care (HBHC) patients homogeneously by their characteristics with respect to cost of care to develop alternative case mix methods for management and reimbursement (allocation) purposes. Six Veterans Affairs (VA) HBHC programs in Fiscal Year (FY) 1986 that maximized patient, program, and regional variation were selected, all of which agreed to participate. All HBHC patients active in each program on October 1, 1987, in addition to all new admissions through September 30, 1988 (FY88), comprised the sample of 874 unique patients. Statistical methods include the use of classification and regression trees (CART software: Statistical Software; Lafayette, CA), analysis of variance, and multiple linear regression techniques. The resulting algorithm is a three-factor model that explains 20% of the cost variance (R2 = 20%, with a cross validation R2 of 12%). Similar classifications such as the RUG-II, which is utilized for VA nursing home and intermediate care, the VA outpatient resource allocation model, and the RUG-HHC, utilized in some states for reimbursing home health care in the private sector, explained less of the cost variance and, therefore, are less adequate for VA home care resource allocation.

Aftercare↗
PubMed1991

[Plastic surgery measures in combined soft tissue defects of the lower leg].

Isolated or combined soft tissue defects of the lower leg are still a challenge as regard diagnostic and differential treatment. We distinguish acute and chronic isolated or combined soft tissue defect. Acute trauma within a multiple injury pattern is a special form of the acute soft tissue defect. For diagnostic purposes we use a preoperative and intraoperative standardized diagnostic programme. A new classification oriented towards the therapeutic procedure is presented, as is therapy algorithm which has been created.

Follow-Up Studies↗
PubMed1992

Multiple dipole modeling and localization from spatio-temporal MEG data.

An array of biomagnetometers may be used to measure the spatio-temporal neuromagnetic field or magnetoencephalogram (MEG) produced by neural activity in the brain. A popular model for the neural activity produced in response to a given sensory stimulus is a set of current dipoles, where each dipole represents the primary current associated with the combined activation of a large number of neurons located in a small volume of the brain. An important problem in the interpretation of MEG data from evoked response experiments is the localization of these neural current dipoles. We present here a linear algebraic framework for three common spatio-temporal dipole models: i) unconstrained dipoles, ii) dipoles with a fixed location, and iii) dipoles with a fixed orientation and location. In all cases, we assume that the location, orientation, and magnitude of the dipoles are unknown. With a common model, we show how the parameter estimation problem may be decomposed into the estimation of the time invariant parameters using nonlinear least-squares minimization, followed by linear estimation of the associated time varying parameters. A subspace formulation is presented and used to derive a suboptimal least-squares subspace scanning method. The resulting algorithm is a special case of the well-known MUltiple SIgnal Classification (MUSIC) method, in which the solution (multiple dipole locations) is found by scanning potential locations using a simple one dipole model. Principal components analysis (PCA) dipole fitting has also been used to individually fit single dipoles in a multiple dipole problem. Analysis is presented here to show why PCA dipole fitting will fail in general, whereas the subspace method presented here will generally succeed. Numerically efficient means of calculating the cost functions are presented, and problems of model order selection and missing moments are discussed. Results from a simulation and a somatosensory experiment are presented.

Algorithms↗
PubMed1977

[Interpretation of pulse curves by means of the Walsh analysis].

A method for classification of medical data using the Walsh transformation is demonstrated. The Walsh spectrum was obtained by the algorithm of Andrews-Kane-Pratt. The spectral points were used to declare the signals normal or abnormal. The example described in this paper shows that in the case of pulse wave the classification is successful in 93 percent.

Carotid Arteries↗
PubMed1992

Generation of a substructure library for the description and classification of protein secondary structure. I. Overview of the methods and results.

Protein secondary structure has been typically classified into four major classes--alpha-helices, extended strands, reverse turns, and loops. Available methods for secondary structure analysis utilize predefined structure templates to search for structural matches among proteins. By this approach a significant portion of a proteins backbone conformation is assigned to one of a limited number of conformations or, if unassigned, to random coil. To expand our ability to describe protein secondary structure, we have developed an algorithm that operates independently of a predefined structure template. The procedure uses two geometric descriptors, the linear distance and the backbone dihedral angle, to represent the conformation form the alpha-carbon coordinates. The algorithm functions by searching for conformationally equivalent, contiguous fragments without regard to secondary structural classification and is thus independent of the complexity of the backbone fold. The result is a library of conformationally equivalent structure fragments that exhibit some novel characteristics. The library contains features that reproduce the major secondary structure classes as well as defining conformations previously described only as random or undefined conformations. Additionally, the library defines several subclassifications of beta-strands. We present here a validation of this method and a presentation and discussion of the most significant results. In a second study, we report the results of application of this method to spectra-structure correlations in Fourier transform infrared spectroscopy.

Algorithms↗
PubMed1992

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.

Algorithms↗