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Results for “Multiple Classification Analysis”

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At least 235 records · Page 13Linked to original sources
PubMed1997

A rule-based expert system for the automatic classification of DNA "ploidy" histograms measured by the CAS 200 image analysis system.

DNA "ploidy" histogram interpretation is one of the most important sources of variation in DNA image cytometry and is influenced by multiple technical factors such as scaling, selection of peaks, and variable classification criteria. A rule-based expert system was developed to automate and eliminate subjectivity from this interpretative process. Ninety-eight Feulgen stained histologic sections from patients with breast, colon, and lung cancer were measured with the CAS 200 image analysis system (Becton Dickinson, Santa Clara, CA); they included diploid (n = 42), aneuploid (n = 46), tetraploid (n = 7), and multiploid (n = 3) examples. The data was converted from listmode format into ASCII with the aid of CELLSHEET software (JVC Imaging, Elmhurst, IL). Individual microphotometric nuclear measurements were sorted to one of 64 bins based on DNA index. The 64 bins were then divided into 5 semi-arbitrarily defined ranges: hypodiploid, diploid, aneuploid, tetraploid, and hypertetraploid. The nuclear percentages in each range were calculated with EXCEL 4.0 (Microsoft, Redmond, WA). The histograms were divided into 2 equal sets: training and testing. The data from the training set were used to develop 16 IF-THEN rules to classify the histograms into diploid, aneuploid, or tetraploid. A macro was programmed in EXCEL to automate all these operations. The rule-based expert system classified correctly 45/50 histograms of the training set. Two tetraploid histograms were classified as aneuploid. Three multiploid histograms were classified as tetraploid. All histograms in the testing set were correctly classified by the expert system. The potential role of rule-based expert system technology for the objective classification of DNA "ploidy" histograms measured by image cytometry is discussed.

Automation↗
PubMed1991

Association between neuroepithelial tumor and multiple intestinal polyposis (Turcot's syndrome): report of a case and critical analysis of the literature.

We report a case of association of a brain tumor with multiple intestinal polyposis (Turcot's syndrome) and offer a critical analysis of the relevant literature with a view to revising the classification of the syndrome in relation to familial multiple polyposis and Gardner's syndrome. For this purpose, we considered only cases of intestinal polyposis associated with a primary neuroepithelial tumor (medulloblastoma, glioma, or glioblastoma) as originally described by Turcot. Differences emerged, depending on the central nervous system tumor type, which suggests that this neoplastic association may be classified as two distinct syndromes.

Adenomatous Polyposis Coli↗
PubMed2004

Marker identification and classification of cancer types using gene expression data and SIMCA.

OBJECTIVES: High-throughput technologies are radically boosting the understanding of living systems, thus creating enormous opportunities to elucidate the biological processes of cells in different physiological states. In particular, the application of DNA micro-arrays to monitor expression profiles from tumor cells is improving cancer analysis to levels that classical methods have been unable to reach. However, molecular diagnostics based on expression profiling requires addressing computational issues as the overwhelming number of variables and the complex, multi-class nature of tumor samples. Thus, the objective of the present research has been the development of a computational procedure for feature extraction and classification of gene expression data. METHODS: The Soft Independent Modeling of Class Analogy (SIMCA) approach has been implemented in a data mining scheme, which allows the identification of those genes that are most likely to confer robust and accurate classification of samples from multiple tumor types. RESULTS: The proposed method has been tested on two different microarray data sets, namely Golub's analysis of acute human leukemia and the small round blue cell tumors study presented by Khan et al.. The identified features represent a rational and dimensionally reduced base for understanding the biology of diseases, defining targets of therapeutic intervention, and developing diagnostic tools for classification of pathological states. CONCLUSIONS: The analysis of the SIMCA model residuals allows the identification of specific phenotype markers. At the same time, the class analogy approach provides the assignment to multiple classes, such as different pathological conditions or tissue samples, for previously unseen instances.

Biomarkers, Tumor↗
PubMed2003

Discriminant validity and relative precision for classifying patients with nonspecific neck and back pain by anatomic pain patterns.

STUDY DESIGN: Secondary analysis of a previously described cohort of prospective, consecutive patients with acute neck or low back pain referred to outpatient rehabilitation was performed. OBJECTIVE: To estimate discriminant validity and relative precision of two classification procedures (first visit vs multiple visit) in discriminating short-term pain intensity and perceived disability outcomes. SUMMARY OF BACKGROUND DATA: Centralization and noncentralization are pain responses used to classify patients and predict outcomes. Different time frames have been proposed for operationally defining these responses, which are problematic for comparing outcomes across clinical trials. Classifying patients according to pain response observed from initial examination (first visit) and over time (multiple visits) influences prevalence within categories and interpretation of classification usefulness, which merits further investigation. METHODS: Patients with acute onset of nonspecific neck or low back pain referred to two outpatient physical therapy clinics completed body pain diagrams, pain intensity ratings, and disability questionnaires at initial evaluation, during each visit, and at discharge. Therapists collected data enabling patient classification on initial examination and throughout treatment. Differences in pain and disability from intake to discharge from rehabilitation across classification categories were used to assess discriminant validity. Relative precision was estimated by determining ratios of analysis of covariance F values between classification procedures for pain and disability. RESULTS: Both classification procedures discriminated categories for change in pain and disability. The multiple-visit classification procedure was more precise for discriminating outcomes than the first-visit classification procedure. CONCLUSION: Multiple-visit classification of patients into specific pain pattern subgroups is recommended when pain intensity and disability outcomes are of interest.

Adult↗
PubMed2005

Multiple SVM-RFE for gene selection in cancer classification with expression data.

This paper proposes a new feature selection method that uses a backward elimination procedure similar to that implemented in support vector machine recursive feature elimination (SVM-RFE). Unlike the SVM-RFE method, at each step, the proposed approach computes the feature ranking score from a statistical analysis of weight vectors of multiple linear SVMs trained on subsamples of the original training data. We tested the proposed method on four gene expression datasets for cancer classification. The results show that the proposed feature selection method selects better gene subsets than the original SVM-RFE and improves the classification accuracy. A Gene Ontology-based similarity assessment indicates that the selected subsets are functionally diverse, further validating our gene selection method. This investigation also suggests that, for gene expression-based cancer classification, average test error from multiple partitions of training and test sets can be recommended as a reference of performance quality.

Algorithms↗
PubMed2006

Fatigue is a prevalent and severe symptom associated with uncertainty and sense of coherence in patients with chronic heart failure.

INTRODUCTION: Fatigue is a common symptom in patients with chronic heart failure (CHF) and has a major impact on their daily life activities. The purpose of this study was to examine the prevalence and severity of fatigue, conceptualized as a multiple dimensional symptom, and to determine the influence of sense of coherence and uncertainty on the fatigue experience in patients with CHF. METHODS: Ninety-three consecutive patients, hospitalized with a diagnosis of CHF, completed the Multidimensional Fatigue Inventory Scale (MFI-20), Cardiovascular Population Scale (CPS), and Sense of Coherence Scale (SOC) and were classified according to the New York Heart Association (NYHA) functional classification criteria. Associations between selected variables were explored with multiple regression analysis. RESULTS: The patients reported high prevalence and severity in the physical dimensions of fatigue. Uncertainty was associated positively with tiredness and reduced functional status. High age predicted reduced motivation and the ability to concentrate were affected by low SOC. CONCLUSION: Fatigue is a prevalent and distressing experience in patients with CHF, where a variety of factors influence different dimensions of the fatigue experience. Recognising this, symptom management must be directed towards comprehensive assessment and a broad approach in interventions aimed at alleviating fatigue.

Activities of Daily Living↗
PubMed2002

An investigation of factors predictive of independence in transfers and ambulation after hip fracture.

OBJECTIVES: To compare the predictive value of measurements of mobility on the second day postsurgery with previously established outcome predictors after hip fracture and to establish a statistical model for the prediction of independence in transfers and ambulation. DESIGN: Prospective, validation cohort study. SETTING: Primary care center. PATIENTS: Two samples of 50 patients admitted with primary diagnosis of hip fracture. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Independence in transfers and ambulation within 2 weeks of surgery. Predictor variables considered were age, mental state, prefracture mobility, and 4 measurements of transfers and ambulation on the second day postsurgery. RESULTS: In bivariate logistic regression analysis, all variables were significant predictors. In multiple logistic regression analysis, only distance walked and assistance required in transferring supine to sitting on day 2 postsurgery were significant. The multiple logistic regression model produced from the analysis had an outcome classification accuracy of 88% when tested on an independent sample. CONCLUSIONS: Measurements of mobility on day 2 postsurgery are significant and reliable predictors of independence in transfers and ambulation. Further consideration of the variables age, mental state, and prefracture mobility do not appear to improve the accuracy of the prediction.

Activities of Daily Living↗
PubMedDate not supplied

[Does geometry of the lumbosacral inclination have an effect on the etiology of isolated osteochondrosis of L5/S1?].

Men and women with isolated osteochondrosis L5/S1 (excluding transitional anomalies) were compared against a corresponding group of healthy volunteers to see whether there is any geometric or statistical evidence that might constitute predisposing factors for isolated osteochondrosis L5/S1. Arithmetic means, variances, standard deviations, and correlation coefficients were calculated for all the characteristics determined for the two groups. Multiple linear discriminant analysis was used to try to reproduce any classifications our groupings of the characteristic bearers on the basis of their characteristics. It was found that the position of the sacrum in the pelvis and the extent of lumbar lordosis play a major role. To detect a predisposition for isolated osteochondrosis L5/S1, it is thus necessary to evaluate: the position of the sacrum with regard to the pelvis and the degree of lumbar lordosis-excluding that of the fifth lumbar vertebra-in the angle system. This evaluation can be performed by measuring the dorsal inclination of the sacrum (the delta angle) and the Albrecht inclination.

Adolescent↗
PubMed2005

Cortical sources of CRF, NKB, and CCK and their effects on pyramidal cells in the neocortex.

In order to investigate how neuropeptide transmission can modulate the neocortical network, we mapped the expression of neurokinin (NK) B, cholecystokinin (CCK), and corticotropin-releasing factor (CRF) and their receptors to neuronal types using patch-clamp and single-cell reverse transcription-polymerase chain reaction in acute slices of rat neocortex. Classification of neurons by unsupervised clustering based on the analysis of multiple electrophysiological and molecular properties disclosed 3 GABAergic interneuron clusters and 1 pyramidal cell cluster. The 3 neuropeptides were expressed in a cluster of interneurons characteristically expressing vasoactive intestinal peptide. CRF was additionally found in a cluster containing almost exclusively somatostatin-expressing interneurons, whereas CCK was present in all clusters. The respective receptors of these peptides, NK-3, CCK-B, and CRF-1, were essentially expressed in pyramidal cells. At -60 mV, pyramidal cells were weakly depolarized by each of these peptides. When pyramidal neurons were maintained to about 5 mV below spike threshold, depolarization induced by each peptide resulted in a long-lasting action potential discharge. Neuropeptide effects were prevented by selective antagonists of NK-3, CCK-B, and CRF-1 receptors. These results suggest that pyramidal neurons are the primary target of NKB, CCK, and CRF in the neocortex. They further indicate that specific interneuron types coordinate the release of these peptides and can induce a long-lasting increase of the excitability of the neocortical network.

Action Potentials↗
PubMed2005

Effects of defect configuration, size, and remaining teeth on masticatory function in post-maxillectomy patients.

The aim of this study was to investigate the correlation between the masticatory function and the maxillary defect configuration, size, and remaining teeth in post-maxillectomy patients restored with an obturator prosthesis. Fifty consecutive post-maxillectomy patients (mean age 67.0) participated in this study. The subjects consisted of 26 dentate and 24 edentulous patients. Data were collected from the patients' clinical records, diagnostic casts, and a questionnaire on masticatory function to evaluate the defect configuration, size, and the masticatory function scores associated with wearing obturator prostheses. The defect size was evaluated by the ratio of defect area to the horizontal impression area. The defect configuration was assessed according to Aramany's classification and separated into unilateral and bilateral defects. The multiple regression analysis and the Mann-Whitney U-test (P<0.05) were used to assess statistical significance. The Spearman's correlation coefficient by rank test was also used to detect correlation. The following conclusions were made: (i) The presence of teeth in the maxillary dentition and the different type of the defect configuration had significant correlation with the masticatory function score (r=0.616). (ii) The masticatory function scores of the subjects differed significantly with the presence of teeth in the maxillary dentition and the different types of defect configurations (P=0.005, P=0.002, respectively). (iii) There was significant correlation between the masticatory function score and the size of the defect area in the edentulous group (r=-0.648, P=0.001). The presence of teeth, the size and configuration of the defect influenced the masticatory function of post-maxillectomy patients with obturator prostheses.

Adult↗
PubMed1999

Full second-order chromatographic/spectrometric data matrices for automated sample identification and component analysis by non-data-reducing image analysis.

A data analysis method is proposed for identification and for confirmation of classification schemes, based on single- or multiple-wavelength chromatographic profiles. The proposed method works directly on the chromatographic data without data reduction procedures such as peak area or retention index calculation. Chromatographic matrices from analysis of previously identified samples are used for generating a reference chromatogram for each class, and unidentified samples are compared with all reference chromatograms by calculating a resemblance measure for each reference. Once the method is configured, subsequent sample identification is automatic. As an example of a further development, it is shown how the method allows identification of characteristic sample components by local similarity calculations thus finding common components within a given class as well as component differences between classes from the reference chromatograms. This feature is a valuable aid in selecting components for further analysis. The identification method is demonstrated on two data sets: 212 isolates from 41 food-borne Penicillium species and 61 isolates from 6 soil-borne Penicillium species. Both data sets yielded over 90% agreement with accepted classifications. The method is highly accurate and may be used on all sorts of chromatographic profiles. Characteristic component analysis yielded results in good agreement with existing knowledge of characteristic components, but also succeeded in identifying new components as being characteristic.

Chromatography↗
PubMed2004

Multi-class cancer subtype classification based on gene expression signatures with reliability analysis.

Differential diagnosis among a group of histologically similar cancers poses a challenging problem in clinical medicine. Constructing a classifier based on gene expression signatures comprising multiple discriminatory molecular markers derived from microarray data analysis is an emerging trend for cancer diagnosis. To identify the best genes for classification using a small number of samples relative to the genome size remains the bottleneck of this approach, despite its promise. We have devised a new method of gene selection with reliability analysis, and demonstrated that this method can identify a more compact set of genes than other methods for constructing a classifier with optimum predictive performance for both small round blue cell tumors and leukemia. High consensus between our result and the results produced by methods based on artificial neural networks and statistical techniques confers additional evidence of the validity of our method. This study suggests a way for implementing a reliable molecular cancer classifier based on gene expression signatures.

Artificial Intelligence↗
PubMed1983

The diagnosis and classification of multiple sclerosis: evoked responses and spinal fluid electrophoresis.

Multimodality evoked responses (including visual, brainstem auditory, and somatosensory) and CSF analysis were evaluated in 123 patients grouped into definite, probable, and possible MS according to the McAlpine criteria. The evoked responses (ERs) were very sensitive in detecting asymptomatic lesions and can therefore be used in conjunction with clinical data to provide evidence of multiple lesions. The CSF abnormalities also have high sensitivity and specificity in MS. ER and CSF findings, therefore, should be considered in addition to the clinical data in any classification of MS.

Adolescent↗
PubMed2006

FlgM anti-sigma factors: identification of novel members of the family, evolutionary analysis, homology modeling, and analysis of sequence-structure-function relationships.

FlgM proteins, also known as Anti-sigma-28 factor (sigma28), are negative regulators of flagellin synthesis. Recently, a three-dimensional structure of the Aquifex aeolicus sigma28/FlgM complex (PDB code: 1rp3) was determined by X-ray crystallography at 2.3 A resolution. Furthermore, experimental data on bacterial FlgM, including site-directed mutagenesis and structural characterization by NMR are also available. However, an interpretation of the sequence-structure-function relationships combining X-ray and NMR data with the evolutionary information extracted from the increasing number of FlgM-related sequences annotated in databases is not available. In the present study, we combined database sequence searches and sequence-analysis tools to update the multiple sequence alignment of a previously characterized cluster of orthologs (COG2747) and the PFAM classification of protein domains (PF04316) for the FlgM family. A phylogenetic analysis of 77 protein sequences revealed the presence of at least three major sequence clades within the FlgM family. Besides, we predicted functional residues using a SequenceSpace method. We also generated homology models for Bacillus subtilis and Salmonella typhimurium FlgM proteins, for which sequence-structure-function relationship data are available, and used the docking program ClusPro to hypothesize about the dimer association between FlgM proteins. In conclusion, the analysis presented in this work will be useful in designing new experiments to understand better protein-protein interactions between FglM, sigma factors, and putative molecules from the flagellar export apparatus. Electronic Supplementary Material is available in the online version of this article at http://link.springer.de/

Bacterial Proteins↗
PubMed1986

On robust partial discriminant analysis as a decision-making tool with clinical and analytical chemical data.

Classification is one of the fundamental goals of science and is basic to the diagnosis of disease. Unfortunately, classifying objects (e.g., patients) on the basis of clinical and/or laboratory experimental observations into various groups can be difficult when the groups overlap or contain outlying points. Recently, Broffitt, Randles, and co-workers proposed a procedure, robust partial discriminant analysis (RPDA) for dealing with such problems, but testing of the procedure was limited to Monte Carlo simulation. In this study, RPDA was applied to real data, in order to compare its effectiveness with ordinary discriminant analysis, as well as to determine if RPDA was a suitable procedure to use to classify chemical compounds on the basis of experimental observations and as a tool in the diagnosis of disease (in particular, multiple sclerosis and thyrotoxicosis), with data based on experimental and clinical observations. The resulting RPDA classifications were an improvement over those obtained from ordinary discriminant analysis.

Aldehydes↗
PubMed1999

Model based classification of cardiovascular response patterns.

A comprehensive analysis of cardiovascular control (CVC) patterns with multiple subjects is presented. It became feasible by recent methodological advances. Simple computer models were generated automatically, reproducing only factors of the true model that are relevant to the focus if investigation. These models--named aspect-models--could in turn be used in model individualization, thus reducing the necessary computational amount. The achieved speedup by a factor of more than three thousand and the high numerical stability of the resulting method allows the unsupervised identification of a large body of experimental data. The analysis of tilt table experiments of 18 subjects revealed a remarkable variety of reaction patterns. Closer examination yielded different classes of subjects. Two main groups corresponding to basic types of CVC were observed. Three outliers could be assigned to the specific situation of some subjects.

Adult↗
PubMedDate not supplied

Newborn screening for congenital hypothyroidism, Victoria, Australia, 1977-1997. Part 2: Treatment, progress and outcome.

A controlled longitudinal prospective study is reported of physical and neuropsychological progress up to 12 years in 152 children with congenital hypothyroidism (CH), detected by newborn screening in the Australian state of Victoria and born between the onset of screening in mid-1977 and December 1988. Linear growth of the CH children was normal. Throughout they were slightly heavier and the median head circumference was slightly larger compared with reference data. Those with thyroid aplasia required a marginally larger dose of thyroxine to achieve euthyroidism. Assessment of cognitive outcome in the children with permanent primary CH revealed the mean scores at 2, 5 and 8 years to be from 8.5 (p<0.001) to 10.2 (p<0.001) points lower than in a group of 60 euthyroid controls. However, there was large overlap and, of the affected children, only 10.1% at 2 years, 3.9% at 5 years and 6.8% at 8 years fell more than 2 SD below the means of the euthyroid controls. On univariate analysis, variables shown to have significant correlation with cognitive outcome at 8 years in the CH children were newborn activity, baseline TT4 and FTI, initial T4 dosage, socio-economic classification, maternal age, maternal education and presence of a serious accompanying disorder. On multiple regression analysis, significant variables were baseline bone age, maternal age and education, and presence of a serious accompanying disorder. No single thyroidal or extra-thyroidal variable could be identified to account for the discrepancy between the children with CH and the controls.

Age Determination by Skeleton↗