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PubMed1981

The look-up table: a classifier for cell sorters.

Currently used classifiers for flow cell sorters are described and the look-up table is introduced as such. An experimental setup of a look-up table classifier added to a commercially available cell sorter, under control of a microcomputer is described. The contents of the look-up table are obtained from contours of regions of interest. These regions are defined by the user who designates the areas on a video color display of the bivariate flow data. Since most cell clusters form elliptic or ovoid shapes in a multi-dimensional feature space this method enables a better matching of window shapes to cluster outlines, compared to conventional sort decision circuitry.

Cell Separation↗
PubMed1981

The effect of abnormal cell proportion on specimen classifier performance.

In two previous papers we developed formulas relating the performance (error rates) of a two-class specimen classifier to the performance of a preceding two-class classifier and the number of cells examined (K. R. Castleman and B. S. White, Analytical and Quantitative Cytology 2:117, 1980 and K. R. Castleman and B. S. White, Cytometry 1:156, 1980.). This analysis assumed a certain proportion (p) of abnormal cells on an abnormal specimen. In this paper we examine what happens when a system designed assuming one value of p is presented with a positive specimen having a different abnormal cell proportion. We show that the specimen false negative error rate increases dramatically as p decreases below the design value, and conversely. This suggests that the specimen classification performance of a particular system should be quoted only with reference to the abnormal cell proportion of the specimens used for testing.

Cell Separation↗
PubMed1987

Improved model for specimen classification based on single-cell classifiers.

We consider probabilistic models for specimen classification procedures based on systems which classify individual cells as normal or abnormal. The models which we consider generalize those discussed previously by Castleman and White (Anal. Quant. Cytol. 2:117-122, 1980; Cytometry 2:155-158, 1981) and by Timmers and Gelsema (Cytometry 6:22-25, 1985). In particular, they include the biologically plausible possibility that the specimen contains cells which are intermediate between the extremes of normal and abnormal. We find that if these additional cells occur differentially in normal and abnormal specimens, then specimen classification can become substantially more efficient when the cell classifier has different error rates for these cells.

Cervix Uteri↗
PubMed1996

The use of amino acid patterns of classified helices and strands in secondary structure prediction.

Elements of secondary structure from known protein three-dimensional structures have been classified with respect to their environments in tertiary structures. The size of the solvent-inaccessible face of an alpha-helix and the accessibility patterns on the two sides of a beta-strand have been used to classify the secondary structures. For each class, we have derived a sequence template, giving the amino acid propensity at each position. A prediction is made by calculating the compatibility of segments of polypeptide sequence against templates for each type of secondary structure. This method predicts not only position of a secondary structure in a protein sequence but also the orientation of the secondary structure with respect to the core of the protein tertiary structure. A jack-knife test is applied to 78 proteins of known structure solved at better than 2 A resolution. It shows that this method predicts between 13% and 17% better than the methods of Lim, GOR and Chou and Fasman at the level of secondary structure. The orientations of inaccessible faces are predicted within 50 degrees of correct value for about two-thirds of alpha-helices.

Adenylate Kinase↗
PubMed1996

Carcinoembryonic antigen, tissue polypeptide antigen and neuron-specific enolase pleural levels used to classify small-cell and non-small-cell lung cancer patients by discriminant analysis.

The classification of lung cancer into small-cell lung cancer (SCLC) and non-small-cell lung cancer (NSCLC) is essential for disease prognosis and treatment. For this purpose, we have tried to optimize the use of three tumour markers determined on pleural effusions, to differentiate SCLC from NSCLC by means of a canonic variable, generated by discriminant analysis, including subjects with histologically proven lung cancer. Discriminant analysis was performed by using carcinoembryonic antigen, neuron-specific enolase and tissue polypeptide antigen pleural levels, determined in 65 consecutive and unselected patients, histologically classified as 49 NSCLC and 16 SCLC. To validate the formula generated, a control group of 37 lung cancer patients (10 SCLC and 27 NSCLC), enrolled subsequently, was employed. Applying the discriminant analysis to SCLC and NSCLC patients a good classification was obtained (92% rate of correct classification). The aforementioned formula, applied to the validation group, showed a 92% rate of correct classification. This method, which is rapid, inexpensive and routinely applicable to malignant pleural effusions, may be reliably used to classify lung cancer patients.

Adult↗
PubMed1994

Comparison of the polymerase region of small round structured virus strains previously classified in three antigenic types by solid-phase immune electron microscopy.

We have used a reverse transcription-polymerase chain reaction with nested sets of primers to determine the nucleotide sequences of a 166 base pair segment of the RNA polymerase region of seven strains of small round structured viruses (SRSVs) from the United Kingdom. These SRSV strains were previously classified by solid-phase immune electron microscopy into three antigenic types--UK2, UK3 and UK4, which are comparable to the prototype strains Norwalk virus, Hawaii agent, and Snow Mountain agents, respectively. Based on their sequences, the seven strains from the United Kingdom could be divided into two groups. The first group included two strains of the UK2 type along with Norwalk virus and Southampton virus and the second group included three strains of UK3 and two strains of UK4 types. Viruses in the first group showed 75.3%-77.1% nucleotide and 89.1%-94.6% amino acid identity with Norwalk virus while those of the second group showed 60.8%-63.3% nucleotide and 67.3%-69.1% amino acid identity. Nucleotide and amino acid identity within the second group ranged between 91.6%-99.4% and 96.4%-100%, respectively. These results suggest that the SRSVs antigenically related with Norwalk virus, Hawaii agent, and Snow Mountain agent, can be classified into two genotypes on the basis of their sequences in the RNA polymerase region.

Adult↗
PubMed1994

The development of a decision support system for the pathological diagnosis of human cerebral tumours based on a neural network classifier.

This study describes the use of a topological mapping system in the classification of cerebral tumours and the development of a decision support system based upon that classifier. Fourteen pathological parameters from two hundred primary cerebral tumours are presented as vectors to a topological map. The map, consisting of a grid of neurones, learns the features of each tumour by means of a shortest Euclidean distance algorithm, after which self adaptation of the neurons occurs. An LVQ algorithm performs the final classification. Study of the map reveals that it can correctly classify tumors following their malignancy potential and their cytogenesis. The decision support system uses the network at its core and helps not only in reaching a diagnosis but also in finding the optimal way to reach that diagnosis. The usefulness of such a mapping system lies in the field of education, clinical research and medically acceptable cost reduction.

Algorithms↗
PubMed1991

[Schmuth's group findings--a simple system for classifying dysgnathias].

The advantages and disadvantages of Schmuth's findings, which classify eugnathic as well as dysgnathic dentition are opposed to Angle's classification. Using Schmuth's findings is a way of classifying without ignoring the physiological variability in the area of the first molars, which can lead to false diagnosis. 386 models were examined at the beginning of the patients' treatment. The results are discussed.

Dental Occlusion↗
PubMed1996

Classifying general medicine readmissions. Are they preventable? Veterans Affairs Cooperative Studies in Health Services Group on Primary Care and Hospital Readmissions.

OBJECTIVES: To describe a new quality assessment method used to classify the preventability of hospitalization in terms of patient, clinician, or system factors. DESIGN: The instrument was developed in two phases. Phase 1 was a prospective comparison of admitting residents' and their attending physicians' classifications of the perceived preventability of consecutive admissions to one Veterans Affairs Medical Center (VAMC) excluding admissions to the intensive care unit (ICU). In phase 2, a panel of 10 physicians rated 811 abstracted records of readmissions from nine VAMCs. SETTING: Nine VAMCs across the United States with varying degrees of university hospital affiliation. PATIENTS: Phase 1, 156 patients admitted to the general medicine service at the Durham VAMC. Phase 2, 514 patients accounting for 811 readmissions within 6 months of a general medicine service discharge at nine VAMCs. MEASUREMENTS AND MAIN RESULTS: Physicians used a checklist to record the reason for hospitalization, the preventability of the hospitalization, and, if preventable, a reason defining preventability, which was classified in terms of system, clinician, and patient factors. In phase 2, two physician panelists assessed preventability for each chart. When two panelists disagreed on the preventability of hospitalization, a third panelist, blind to the original assessments, rated the chart. In phase 1, residents and attending physicians rated 33% and 34% of admissions as preventable (kappa = 0.41), respectively. In phase 2, 277 (34%) of 811 readmissions were deemed preventable. Intraobserver accuracy for the assessment of preventability was 96% (kappa = 0.89). interobserver accuracy was 73% (kappa = 0.43). Hospital system factors accounted for 37% of preventable readmissions, clinician factors for 38%, and patient factors for 21%. The nine hospitals differed markedly in their profile of reasons for preventable readmissions (p = .005). CONCLUSIONS: Using a new method of determining the preventability of hospitalizations, we identified several factors that might avert hospitalizations. Focusing efforts to identify preventable hospitalizations may yield better methods for managing patients' total health care needs; however, the content of those efforts will vary by institution.

Adult↗
PubMed1992

An overview of principles for classifying brain tumors.

The purpose of this review is to clarify for the nonneuropathologist some of the confusing issues concerning the classification of brain tumors. Following a short discussion of the commonly used methods to diagnose brain tumors clinically (frozen section, light and electron microscopy, immunohistochemistry), the general principles of classifying neural tumors are presented. Grading of tumors on the basis of histological anaplasia, and the concept that tumor cells can be related to specific cytological stages of normal cellular development (cytogenetic classification) are presented. The World Health Organization system of classifying neural tumors is an attempt to develop a standardized classification scheme with as few interpretative controversies as possible, but it has required revision as new information has been gained. The major clinical and biological features of the commonest tumor groups are then discussed. It is unlikely that improvements in the classification of brain tumors will be based solely on histological information. Definitions of tumor entities that will provide more accurate prognoses and bases for effective therapy will require considerably more information at the molecular level than is currently available.

Astrocytoma↗
PubMed1995

Proposal of a tiered approach to assessing and classifying the health risk of exposure to fibres.

The basis of a preventative health policy for humans against potential risks from chemical products is based on risk assessment leading to the classification and labeling of substances. However, the different existing classifications do not give an homogeneous framework that can be used in every country. Therefore, a tiered approach to assessing and classifying the health risk of exposure to fibres is proposed based on the EU Directive on carcinogens. The aim of this paper is to propose an algorithm for the risk assessment of existing and future fibres. Clearly chemically defined respirable fibres should be classified according to an algorithm based on a step-by-step procedure: a priori criteria, screening tests, long-term inhalation tests and epidemiological data (for commercial fibres). Then fibre-containing products should be labelled according to the classification of each type of fibre it contains, on one hand, and the ability of the product to release fibre in the air, on the other. The different tests listed in this algorithm, extensively discussed during the Workshop, are presented in detail in the following paper.

Carcinogenicity Tests↗
PubMed1987

Diagnosis of acute abdominal pain using a three-stage classifier.

The present paper deals with an application of a three-stage classifier based on a decision tree logic to the diagnosis of acute abdominal pain. On the basis of clinical information collected from a series of 476 patients suffering from abdominal pain of acute onset, the method of multistage classifier synthesis is presented. The results of classification accuracy using a modified version of k-nearest neighbours strategy for different features used at interior nodes of a tree are given.

Abdomen, Acute↗
PubMed1991

Fuzzy K-nearest neighbor classifiers for ventricular arrhythmia detection.

We report a study of the efficiency of 4 classifiers (the K-nearest-neighbor and single-nearest-prototype algorithms, each as parametrized by both Fuzzy C-Means and Fuzzy Covariance clustering) in the detection of ventricular arrhythmias in ECG traces characterized by 4 features derived from 7 spectral parameters. Principal components analysis was used in conjunction with a cardiologist's deterministic classification of 90 ECG traces to fix the number of trace classes to 5 (ventricular fibrillation/flutter, sinus rhythm, ventricular rhythms with aberrant complexes and 2 classes of artefact). Forty of the 90 traces were then defined as a test set; 5 different learning sets (numbering 25, 30, 35, 40 and 45 traces) were randomly selected from the remaining 50 traces; each learning set was used to parametrize both the classification algorithms using both fuzzy clustering algorithms and the parametrized classification algorithms were then applied to the test set. Optimal K for K-nearest-neighbor algorithms and optimal cluster volumes for Fuzzy Covariance algorithms were sought by trial and error to minimize classification differences with respect to the cardiologist's classification. Fuzzy Covariance clustering afforded significantly better perception of cluster structure than the Fuzzy C-Means algorithm, and the classifiers performed correspondingly with an overall empirical error ratio of just 0.10 for the K-nearest-neighbor algorithm parametrized by Fuzzy Covariance.

Algorithms↗
PubMed1987

A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.

The objective of this study was to develop a prospectively applicable method for classifying comorbid conditions which might alter the risk of mortality for use in longitudinal studies. A weighted index that takes into account the number and the seriousness of comorbid disease was developed in a cohort of 559 medical patients. The 1-yr mortality rates for the different scores were: "0", 12% (181); "1-2", 26% (225); "3-4", 52% (71); and "greater than or equal to 5", 85% (82). The index was tested for its ability to predict risk of death from comorbid disease in the second cohort of 685 patients during a 10-yr follow-up. The percent of patients who died of comorbid disease for the different scores were: "0", 8% (588); "1", 25% (54); "2", 48% (25); "greater than or equal to 3", 59% (18). With each increased level of the comorbidity index, there were stepwise increases in the cumulative mortality attributable to comorbid disease (log rank chi 2 = 165; p less than 0.0001). In this longer follow-up, age was also a predictor of mortality (p less than 0.001). The new index performed similarly to a previous system devised by Kaplan and Feinstein. The method of classifying comorbidity provides a simple, readily applicable and valid method of estimating risk of death from comorbid disease for use in longitudinal studies. Further work in larger populations is still required to refine the approach because the number of patients with any given condition in this study was relatively small.

Actuarial Analysis↗
PubMed1979

Should 'non-Feighner schizophrenia' be classified with affective disorder?

Narrow definitions of schizophrenia increase homogeneity at the expense of leaving unclassified many patients with shizophrenic symptoms. Family history and follow-up studies indicate that many such patients ought to be classified with those having affective disorders. This study determines morbid risks for affective disorder and schizophrenia in first degree relatives of patients with chart but not research diagnoses of schizophrenia. Comparisons with morbid risk figures for relatives of individuals satisfying research criteria for depression, mania or schizophrenia indicate that the 'non-Feighner schizophrenia' group is probably too heterogenous to be classified entirely as affective disorder or as schizophrenia.

Adolescent↗
PubMedDate not supplied

Evaluation of automated information systems in health care: an approach to classifying evaluative studies.

In this paper we discuss an approach to classifying evaluative studies of automated information systems in health care. Selected literature (76 studies) is classified according to the type of automated information system (based on relationship to the care process), the study design used, the data collection methods used, the effect(s) measured and the type of evaluation (e.g. cost-benefit analysis). First results show that certain types of automated information systems have not been evaluated much, going by the number of studies selected. Furthermore, it is observed that certain study designs (time-series design), data collection methods (modelling and simulation) and effect measures (job satisfaction) are hardly to be found in the literature. Only 10 of 76 selected studies used a type of evaluation for which both consequences and costs are considered. Detailed investigation of the literature may provide information for the development of a general framework for the evaluation of different types of automated information systems.

Classification↗
PubMed1989

The bleeding severity index: validation and comparison to other methods for classifying bleeding complications of medical therapy.

Reports of bleeding complications of medical therapy should be based on valid methods of classification, but the reproducibility of existing methods has not been tested. Therefore, we prospectively studied three methods to classify the severity of bleeding: a purely subjective implicit method, a previously published explicit method using brief criteria, and the bleeding severity index, which is a new explicit method using detailed criteria about the amount, rate, and consequences of bleeding. Three physicians independently reviewed abstracts of 168 patients treated with anticoagulants. The proportion of cases classified as major bleeding varied widely when the implicit method was used (2, 14 and 39%), less when the old explicit method was used (28, 40 and 47%), and not at all when the new bleeding severity index was used (20, 20 and 20%). Intraobserver agreement was excellent for both explicit methods (kappa greater than or equal to 0.95). However, interobserver agreement was better for the bleeding severity index (kappa = 0.87) than for the old explicit method (kappa = 0.69) or the implicit method (kappa = 0.39). We conclude that the classification of bleeding complications of medical therapy depends on the method used. In comparison to older methods, the bleeding severity index is highly reproducible and should be tested more widely to determine whether it can be applied to the burgeoning clinical research in anticoagulation and thrombolysis.

Anticoagulants↗