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PubMed2005

Morphometric discriminant analysis for the classification of Diplectanum (Monogenea: monopisthocotylea), parasites of Sphyraena flavicauda.

The authors have examined the morphology of Diplectanum cazauxi and Diplectanum bauchotae through the observation of 23 specimens (10 of D. cazauxi and 13 of D. bauchotae) found during May 2003 on the gills of 2 specimens of Sphyraena flavicauda Rüppell, 1838 collected at Ras Mohammed National Park, Egypt. A discriminant analysis was performed on the morphometric data of opisthaptor to determine which parameters more accurately distinguish the two species. The best discriminant parameters resulted to be the copulatory apparatus and the central bar, which determined the absence of misclassification in the model. The discriminant functions are reported for the two species.

Animals↗
PubMed1991

Perinatal events and future developmental outcome--assessment of a newborn's individual prognosis. 2. Prediction of outcome on the basis of perinatological data--results of multivariate discriminant analysis.

The aim of the prospective study described in this paper was to elaborate a prognostic screening method which allows to give an individual prognostic estimate for every newborn, with an accuracy acceptable for clinical purposes. This second part informs about the results of multivariate discriminant analysis, using the data from case histories as well as from the clinical and laboratory findings in the neonates (including "criteria of hypoxia"). According to the kind and number of abnormalities found on the occasion of out-patient consultations during the course of the first two years of life, and according to the developmental status reached at the age of two and six years, the children were classified under two alternative groups. Satisfying results were achieved in the discrimination between the groups of six-year-old children. As compared with the literature, the prognostic method proposed in this paper yields a relatively high accuracy of individual predictions, and therefore promises to become a good tool for clinical practice.

Child↗
PubMed1991

[Multiple discriminant analysis for prognosis of refractory anemia].

Forty-eight patients with refractory anemia (RA) were retrospectively analyzed for their prognosis and subclassified into three groups: 12 patients with hematological improvement (A), 23 patients with no changes (B), and 13 patients with progression to RAEB or acute leukemia (C). For all patients, the median survival were 49.2 months, and the rate of leukemic transformation was 16%. The median survivals were 60.6, 32.1, and 17.9 months, respectively, for groups A, B and C. The factors indicating poor prognosis were low reticulocyte counts, low neutrophil alkaline phosphatase activity, low% red cell utilization, high M/E ratio, high blast percentage in the bone marrow and cytological abnormalities in the granulocyte and megakaryocyte series. By using multiple discriminant analysis, we obtained a formula for the prognostic estimation with a discrimination probability of 62.5%. This formula could predict either the patients with good (Y greater than 0.85) or poor (Y less than 0.59) prognosis, and might be useful to select the treatment for this intractable anemia at the time of diagnosis.

Adolescent↗
PubMed1981

Cluster-oriented discriminant analysis; taxonomic classification of the thyroid function.

A computer assisted procedure for the diagnosis of thyroid diseases, based on seven clinical chemical parameters, is proposed. The population studied consisted of 592 consecutive outpatients with a tentative diagnosis of thyroid disease. Thyroxine, triiodothyronine, T3 uptake test, TSH before and after TRH application, its difference and thyroxine binding globulin have been determined. The patients were clinically examined and in each case a Tc-scintigram was obtained. As a first step, 20 biochemical patterns were defined by cluster analysis (pattern cognition). T check how good in grouping process was, linear discriminant analysis was applied after which the reclassification rates were very satisfactory. The clusters found corresponded well to the pathophysiological situations with some exceptions. As a second step, patients were assigned to these patterns by use of the derived discriminant functions (pattern recognition). The proposed method seems to have some advantages over other diagnostic models published hitherto.

Alpha-Globulins↗
PubMed2004

Identification of protein coding regions of rice genes using alternative spectral rotation measure and linear discriminant analysis.

An improved method, called Alternative Spectral Rotation (ASR) measure, for predicting protein coding regions in rice DNA has been developed. The method is based on the Spectral Rotation (SR) measure proposed by Kotlar and Lavner, and its accuracy is higher than that of the SR measure and the Spectral Content (SC) measure proposed by Tiwari et al. In order to increase the identifying accuracy, we chose three different coding characters, namely the asymmetric, purine, and stop-codon variables as parameters, and an approving result was presented by the method of Linear Discriminant Analysis (LDA).

Codon↗
PubMed1979

Discriminant analysis: methods and program.

Because of the disparity in the results obtained using different methods of discriminant analysis, we have written and used a unique program to test them. These methods can be divided into two groups corresponding to a classical probabilistic approach (i.e., Bayesian methods) or a topological approach (i.e., Sebestyen method).

Bayes Theorem↗
PubMed1977

Discriminant analysis, exemplified with quantitative features of endometrium.

In this paper we illustrate the potential usefulness of discriminant analysis as a means of separating groups of patients and aiding in differential diagnosis of an individual patient. Some of the most important problems are discussed. The analysis is performed with various microscopical endometrial features of endometrial biopsies from 4 groups of 7 patients in different hormonal conditions. There is some evidence that a combination of stereological features gives a better separation of the groups than the usual histological examinations.

Biopsy↗
PubMed1985

Discriminant analysis for predicting dystocia in beef cattle. II. Derivation and validation of a prebreeding prediction model.

Discriminant analysis was utilized to derive and validate a model for predicting dystocia using only data available at the beginning of the breeding season. Data were collected from 211 Chianina crossbred cows (2 to 6 yr old) bred to Chianina bulls. A proportionally stratified sampling procedure divided females into an analysis sample (n = 134) on which the model was derived and a hold-out sample (n = 77) on which the prediction model was validated (tested). Variables available during the derivation stage were cow age, cow weight, pelvic height, pelvic width, pelvic area and calf sire. Dystocia was categorized as either unassisted or assisted. Occurrence of dystocia was 17.2 and 18.2% in the analysis and hold-out samples, respectively. All data were standardized to a mean of zero and a variance of one before statistical analysis. The centroid of cows experiencing dystocia differed (P less than .01) from that of cows calving unassisted in the analysis sample. Significant variables were pelvic area and cow age (standardized coefficients = .56 and .51, respectively). This model correctly classified 85.1% of the cows in the analysis sample. This was 13.5% greater than the proportional chance criterion. For model validation, prediction accuracy was 84.4% in the hold-out group, which was 14.2% greater than the proportional chance criterion. However, only 57.1% of the cows that experienced dystocia were correctly classified. Examination of the data revealed that those cows misclassified were 3 yr of age or older.(ABSTRACT TRUNCATED AT 250 WORDS)

Age Factors↗
PubMed1975

A canonical discriminant analysis of post-embryonic development in Notonecta Maculata fabricius (Insecta:Heteroptera).

A multivariate method, canonical discriminant analysis, was used to discern a pattern of growth in Notonecta maculata. A stepwise procedure reduced the 11 metrical characters measured on individuals of both sexes, from the 1st larval stage to the adult, to 4 significant variates which were used in the canonical analysis. The four canonical variates accounted for the meaningful part of the variablity. Relying on bivariate allometry and on an experimentation with a juvenile hormone analogue, each independent direction of variation was related to combined effects of such biological factors as a general growth trend, sex and juvenile hormone.

Analysis of Variance↗
PubMed1996

Recognizing Ullrich-Turner syndrome by discriminant analysis of craniofacial structure.

In the present paper, we propose an efficient strategy for identification of craniofacial anomalies in the Ullrich-Turner syndrome (UTS). Standardized portrait- and profile-photographs were taken of 21 UTS patients with X-monosomy and 21 normal females. Twenty-seven craniofacial parameters were read from the photographs. The data were analyzed by discriminant analysis, a multivariate statistical method. The result was a function represented by a linear combination of all those craniofacial parameters which best separate the two groups. The discriminant function was applied to 15 additional patients with UTS of various cytogenetic types. All 15 patients were classified correctly. The technique facilitates syndrome-recognition and is a contribution toward the study of karyotype-phenotype relations.

Adolescent↗
PubMed1994

Multi-variate stepwise discriminant analysis research affecting portal hypertension's grade factors of liver function.

The ideal time for selecting portal hypertension operation is the accurate judgement of the grade of liver function, yet the present criterion in grading liver function is controversial. 50 patients with 20 factors related to portal hypertension were undergone stepwise discriminant analysis by using SAS software on the IBM/PC computer (significance level alpha = 0.05). The results show that ascites degree prothrombin time (PT), serum total bilirubin, serum albumin content, main portal vein flow are significant factors. In the light of above variates contributing to grading liver function as to establish a discriminant equation, it was found that the total agreement rate between replaceable discrimination and original Child-Pugh classification is 86%. A test for agreement was performed between discriminant and original classification, showing that the two kinds of classification methods have a good agreement rates (Kappa = 0.7856), indicating the discriminant classification is of practical values.

Adult↗
PubMedDate not supplied

[Microvascular disease in diabetics--discrimination analysis of risk factors].

The study concerned 206 diabetic patients, aged 35-54 years, from the urban Kragujevac area. Of this number 40.3 per cent had macrovascular disease, including vascular heart disease (34.9%), diseased leg blood vessels (12.1%) and cerebral stroke (2.4%). According to the results of discriminative analysis of potential risk factors (age, sex, body weight index, cigarette smoking, systolic and diastolic blood pressure, glycemia, triglycerides, lipoproteins, total cholesterol, HDL and LDL cholesterol, onset and duration of diabetes, family history) diabetic patients with macrovascular disease and patients with vascular heart disease predominated in female population with early onset of diabetes and high level of diastolic blood pressure.

Adult↗
PubMed1998

Iterative stepwise discriminant analysis: a meta-algorithm for detecting quantitative sequence motifs.

An algorithm is presented for detecting a quantitative pattern in peptide fragments that bind class II major histocompatibility complex (MHC) molecules. It is referred to as a meta-algorithm because it requires successive applications of Stepwise Discriminate Analysis (SDA). On every iteration the best subsequence candidates are selected from sequences known to bind class II MHC molecules. When SDA compares probable binding subsequences with subsequences known not to bind class II MHC molecules, a quantitative model emerges that is capable of classifying subsequences as binding or non-binding. In an iterative manner, the resultant model is utilized as a criterion for selecting probable binding subsequence candidates. The procedure is repeated until models converge. In the illustrated examples, the final models correctly classify over 95% of the peptides in a database of peptides whose binding affinity for HLA-DR1 is known. The final model can then be used to predict the binding affinity of peptides that have not yet been laboratory tested.

Algorithms↗
PubMed1995

A new algorithm for predicting splice site sequence based on an improvement of categorical discriminant analysis.

The splicing signals which govern the excision of introns are not yet well explained, since actual splice site sequences are to some extent different from the generally accepted consensus sequences. While a quantification method (categorical discriminant analysis: CDA) has been proposed to analyze splice site signals, sample sequences lying in the overlapping region of sample scores are not discriminated well by CDA, thus limiting the predictive ability of this analytical technique. In this paper, we propose a method to improve the performance of CDA, which is applicable to the analysis of 5'-splice site signals in various mammalian genes. The proposed algorithm has revealed a distinct enhancement in the predicting ability compared to that of traditional CDA and could explain point mutations in the 5'-splice site region of rabbit beta-globin gene fairly well.

Algorithms↗
PubMed1997

Relationship between human genotype and phenotype of N-acetyltransferase (NAT2) as estimated by discriminant analysis and multiple linear regression: 1. Genotype and N-acetylation in vivo.

Twenty-six healthy Caucasian subjects were evaluated for polymorphic N-acetyltransferase (NAT2) metabolic activity in vivo by sulfamethazine phenotyping and for their respective NAT2 genotype. Application of discriminant analysis allowed the separation of the rapid and slow acetylators solely on the base of their respective mutation pattern with identical results as achieved by the classical method of discrimination according to the phenotyping results. Multiple linear regression analysis was used to obtain a quantitative relationship between allelic pattern and the phenotypic outcome. It is shown that the computation methods produce relationships enabling the influence of particular mutations and/or allelic configurations on the metabolic activity in vivo to be estimated. This may be important in cases of discordant or overlapping phenotype and genotype results as well as in investigating the NAT2 polymorphism as a risk factor for cancer and other disease in epidemiological studies.

Acetylation↗
PubMed1991

Detection of Helicobacter pylori carriers by discriminant analysis of urea and pH levels in gastric juices.

An alternative approach to the problems inherent in current methods for detecting Helicobacter pylori carriers--that of being generally time-consuming, expensive, and not sufficiently sensitive--was devised by using the urea concentration and pH levels of gastric juices. A linear discriminant analysis of these variables, measured in 54 patients submitted to digestive endoscopy for gastritis, provided a mathematical formula for assigning the subjects (previously classified by other standard methods) to groups of either positive or negative H pylori carriers. The results obtained showed a correct classification in 52 out of 54 cases with only one false negative and one false positive case.

Adult↗
PubMed1998

Sex determination by discriminant analysis of patella measurements.

The authors have analyzed 80 skeletons (40 males and 40 females) from the collection at the Institute of Legal Medicine of the University of Bari belonging to a known contemporary Southern Italian population; time of death was around 1970 and ages ranged from 25 to 80 years. Seven measurements taken on 80 intact, undeformed right patellae (max height, max width, thickness, height and width of the external facies articularis, height and width of the internal facies articularis) were used to determine sex by multivariate discriminant analysis. One function associating two parameters (max width and thickness) obtained the highest value of correct sex determination with a rate of 83.3%; other functions showed a higher percentage of misclassification (up to 17.5%). This study tests the success rate of correct sex prediction based exclusively on patellar dimensions. The discriminant factors carried out by statistical analysis may aid the forensic anthropologist when no other human skeletal remains suitable for sex determination are available.

Adult↗
PubMed1979

Classification of drugs by discriminant analysis using fragment molecular connectivity values.

An investigation was made into the use of linear and quadratic discriminant analysis, along with K nearest-neighbor analysis, in the classification of a set of 51 compounds which were divided into five therapeutic categories. By superimposing each compound on a pattern structure, as first proposed by Cammarata, eight positions were assigned on the molecule. Each position was coded with the numerical value of a descriptor index. Relative molar refraction, which was the index used by Cammarata, was compared with a number of molecular connective indices. For each of the indices studied, it was found that only four of the eight positions contributed significantly to between-class differences. It was also found that first-order molecular connectivity, calculated as the sum of the contributions of each of the bonds joining a given position, resulted in consistently fewer misclassifications as compared with the other indices. Using first-order molecular connectivity, validation procedures were performed on the original set of compounds, on random samples drawn from this set, and on a set of ten compounds not included in the analysis. The results obtained were highly data dependent, but they, nevertheless, suggest that molecular connectivity indices should prove useful in structural classification procedures.

Analysis of Variance↗