Prevalence of hyperuricemia and relation of serum uric acid with cardiovascular risk factors in a developing country.

BACKGROUND: The prevalence of hyperuricemia has rarely been investigated in developing countries. The purpose of the present study was to investigate the prevalence of hyperuricemia and the association between uric acid levels and the various cardiovascular risk factors in a developing country with high average blood pressures (the Seychelles, Indian Ocean, population mainly of African origin). METHODS: This cross-sectional health examination survey was based on a population random sample from the Seychelles. It included 1011 subjects aged 25 to 64 years. Blood pressure (BP), body mass index (BMI), waist circumference, waist-to-hip ratio, total and HDL cholesterol, serum triglycerides and serum uric acid were measured. Data were analyzed using scatterplot smoothing techniques and gender-specific linear regression models. RESULTS: The prevalence of a serum uric acid level >420 micromol/L in men was 35.2% and the prevalence of a serum uric acid level >360 micromol/L was 8.7% in women. Serum uric acid was strongly related to serum triglycerides in men as well as in women (r = 0.73 in men and r = 0.59 in women, p < 0.001). Uric acid levels were also significantly associated but to a lesser degree with age, BMI, blood pressure, alcohol and the use of antihypertensive therapy. In a regression model, triglycerides, age, BMI, antihypertensive therapy and alcohol consumption accounted for about 50% (R2) of the serum uric acid variations in men as well as in women. CONCLUSIONS: This study shows that the prevalence of hyperuricemia can be high in a developing country such as the Seychelles. Besides alcohol consumption and the use of antihypertensive therapy, mainly diuretics, serum uric acid is markedly associated with parameters of the metabolic syndrome, in particular serum triglycerides. Considering the growing incidence of obesity and metabolic syndrome worldwide and the potential link between hyperuricemia and cardiovascular complications, more emphasis should be put on the evolving prevalence of hyperuricemia in developing countries.

Elevated serum uric acid is associated with high circulating inflammatory cytokines in the population-based Colaus study.

BACKGROUND: The relation of serum uric acid (SUA) with systemic inflammation has been little explored in humans and results have been inconsistent. We analyzed the association between SUA and circulating levels of interleukin-6 (IL-6), interleukin-1beta (IL-1beta), tumor necrosis factor- alpha (TNF-alpha) and C-reactive protein (CRP). METHODS AND FINDINGS: This cross-sectional population-based study conducted in Lausanne, Switzerland, included 6085 participants aged 35 to 75 years. SUA was measured using uricase-PAP method. Plasma TNF-alpha, IL-1beta and IL-6 were measured by a multiplexed particle-based flow cytometric assay and hs-CRP by an immunometric assay. The median levels of SUA, IL-6, TNF-alpha, CRP and IL-1beta were 355 micromol/L, 1.46 pg/mL, 3.04 pg/mL, 1.2 mg/L and 0.34 pg/mL in men and 262 micromol/L, 1.21 pg/mL, 2.74 pg/mL, 1.3 mg/L and 0.45 pg/mL in women, respectively. SUA correlated positively with IL-6, TNF-alpha and CRP and negatively with IL-1beta (Spearman r: 0.04, 0.07, 0.20 and 0.05 in men, and 0.09, 0.13, 0.30 and 0.07 in women, respectively, P<0.05). In multivariable analyses, SUA was associated positively with CRP (beta coefficient +/- SE = 0.35+/-0.02, P<0.001), TNF-alpha (0.08+/-0.02, P<0.001) and IL-6 (0.10+/-0.03, P<0.001), and negatively with IL-1beta (-0.07+/-0.03, P = 0.027). Upon further adjustment for body mass index, these associations were substantially attenuated. CONCLUSIONS: SUA was associated positively with IL-6, CRP and TNF-alpha and negatively with IL-1beta, particularly in women. These results suggest that uric acid contributes to systemic inflammation in humans and are in line with experimental data showing that uric acid triggers sterile inflammation.

Validation of a clinical prediction score for ruling out coronary heart disease in primary care patients with chest pain.

Background: A patient's chest pain raises concern for the possibility of coronary heart disease (CHD). An easy to use clinical prediction rule has been derived from the TOPIC study in Lausanne. Our objective is to validate this clinical score for ruling out CHD in primary care patients with chest pain. Methods: This secondary analysis used data collected from a oneyear follow-up cohort study attending 76 GPs in Germany. Patients attending their GP with chest pain were questioned on their age, gender, duration of chest pain (1-60 min), sternal pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the curve (ROC), sensitivity and specificity of the Lausanne CHD score were calculated for patients with full data. Results: 1190 patients were included. Full data was available for 509 patients (42.8%). Missing data was not related to having CHD (p = 0.397) or having a cardiovascular risk factor (p = 0.275). 76 (14.9%) were diagnosed with a CHD. Prevalence of CHD were respectively of 68/344 (19.8%), 2/62 (3.2%), 6/103 (5.8%) in the high, intermediate and low risk category. ROC was of 72.9 (CI95% 66.8; 78.9). Ruling out patients with low risk has a sensitivity of 92.1% (CI95% 83.0; 96.7) and a specificity of 22.4% (CI95% 18.6%; 26.7%). Conclusion: The Lausanne CHD score shows reasonably good sensitivity and can be used to rule out coronary events in patients with chest pain. Patients at risk of CHD for other rarer reasons should nevertheless also be investigated.

Ensemble methods for environmental data modelling with support vector regression

This paper investigates the use of ensemble of predictors in order to improve the performance of spatial prediction methods. Support vector regression (SVR), a popular method from the field of statistical machine learning, is used. Several instances of SVR are combined using different data sampling schemes (bagging and boosting). Bagging shows good performance, and proves to be more computationally efficient than training a single SVR model while reducing error. Boosting, however, does not improve results on this specific problem.

Prediction of free imatinib concentrations based on total plasma concentrations in patients with gastrointestinal stromal tumours.

AIM: Total imatinib concentrations are currently measured for the therapeutic drug monitoring of imatinib, whereas only free drug equilibrates with cells for pharmacological action. Due to technical and cost limitations, routine measurement of free concentrations is generally not performed. In this study, free and total imatinib concentrations were measured to establish a model allowing the confident prediction of imatinib free concentrations based on total concentrations and plasma proteins measurements. METHODS: One hundred and fifty total and free plasma concentrations of imatinib were measured in 49 patients with gastrointestinal stromal tumours. A population pharmacokinetic model was built up to characterize mean total and free concentrations with inter-patient and intrapatient variability, while taking into account α1 -acid glycoprotein (AGP) and human serum albumin (HSA) concentrations, in addition to other demographic and environmental covariates. RESULTS: A one compartment model with first order absorption was used to characterize total and free imatinib concentrations. Only AGP influenced imatinib total clearance. Imatinib free concentrations were best predicted using a non-linear binding model to AGP, with a dissociation constant Kd of 319 ng ml(-1) , assuming a 1:1 molar binding ratio. The addition of HSA in the equation did not improve the prediction of imatinib unbound concentrations. CONCLUSION: Although free concentration monitoring is probably more appropriate than total concentrations, it requires an additional ultrafiltration step and sensitive analytical technology, not always available in clinical laboratories. The model proposed might represent a convenient approach to estimate imatinib free concentrations. However, therapeutic ranges for free imatinib concentrations remain to be established before it enters into routine practice.

Symptomatic intracranial hemorrhage after stroke thrombolysis: comparison of prediction scores.

BACKGROUND AND PURPOSE: Several prognostic scores have been developed to predict the risk of symptomatic intracranial hemorrhage (sICH) after ischemic stroke thrombolysis. We compared the performance of these scores in a multicenter cohort. METHODS: We merged prospectively collected data of patients with consecutive ischemic stroke who received intravenous thrombolysis in 7 stroke centers. We identified and evaluated 6 scores that can provide an estimate of the risk of sICH in hyperacute settings: MSS (Multicenter Stroke Survey); HAT (Hemorrhage After Thrombolysis); SEDAN (blood sugar, early infarct signs, [hyper]dense cerebral artery sign, age, NIH Stroke Scale); GRASPS (glucose at presentation, race [Asian], age, sex [male], systolic blood pressure at presentation, and severity of stroke at presentation [NIH Stroke Scale]); SITS (Safe Implementation of Thrombolysis in Stroke); and SPAN (stroke prognostication using age and NIH Stroke Scale)-100 positive index. We included only patients with available variables for all scores. We calculated the area under the receiver operating characteristic curve (AUC-ROC) and also performed logistic regression and the Hosmer-Lemeshow test. RESULTS: The final cohort comprised 3012 eligible patients, of whom 221 (7.3%) had sICH per National Institute of Neurological Disorders and Stroke, 141 (4.7%) per European Cooperative Acute Stroke Study II, and 86 (2.9%) per Safe Implementation of Thrombolysis in Stroke criteria. The performance of the scores assessed with AUC-ROC for predicting European Cooperative Acute Stroke Study II sICH was: MSS, 0.63 (95% confidence interval, 0.58-0.68); HAT, 0.65 (0.60-0.70); SEDAN, 0.70 (0.66-0.73); GRASPS, 0.67 (0.62-0.72); SITS, 0.64 (0.59-0.69); and SPAN-100 positive index, 0.56 (0.50-0.61). SEDAN had significantly higher AUC-ROC values compared with all other scores, except for GRASPS where the difference was nonsignificant. SPAN-100 performed significantly worse compared with other scores. The discriminative ranking of the scores was the same for the National Institute of Neurological Disorders and Stroke, and Safe Implementation of Thrombolysis in Stroke definitions, with SEDAN performing best, GRASPS second, and SPAN-100 worst. CONCLUSIONS: SPAN-100 had the worst predictive power, and SEDAN constantly the highest predictive power. However, none of the scores had better than moderate performance.

Methods for Estimating Annual Exceedance-Probability Discharges for Streams in Iowa, Based on Data through Water Year 2010, TR-519, 2013

A statewide study was performed to develop regional regression equations for estimating selected annual exceedance- probability statistics for ungaged stream sites in Iowa. The study area comprises streamgages located within Iowa and 50 miles beyond the State’s borders. Annual exceedanceprobability estimates were computed for 518 streamgages by using the expected moments algorithm to fit a Pearson Type III distribution to the logarithms of annual peak discharges for each streamgage using annual peak-discharge data through 2010. The estimation of the selected statistics included a Bayesian weighted least-squares/generalized least-squares regression analysis to update regional skew coefficients for the 518 streamgages. Low-outlier and historic information were incorporated into the annual exceedance-probability analyses, and a generalized Grubbs-Beck test was used to detect multiple potentially influential low flows. Also, geographic information system software was used to measure 59 selected basin characteristics for each streamgage. Regional regression analysis, using generalized leastsquares regression, was used to develop a set of equations for each flood region in Iowa for estimating discharges for ungaged stream sites with 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities, which are equivalent to annual flood-frequency recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively. A total of 394 streamgages were included in the development of regional regression equations for three flood regions (regions 1, 2, and 3) that were defined for Iowa based on landform regions and soil regions. Average standard errors of prediction range from 31.8 to 45.2 percent for flood region 1, 19.4 to 46.8 percent for flood region 2, and 26.5 to 43.1 percent for flood region 3. The pseudo coefficients of determination for the generalized leastsquares equations range from 90.8 to 96.2 percent for flood region 1, 91.5 to 97.9 percent for flood region 2, and 92.4 to 96.0 percent for flood region 3. The regression equations are applicable only to stream sites in Iowa with flows not significantly affected by regulation, diversion, channelization, backwater, or urbanization and with basin characteristics within the range of those used to develop the equations. These regression equations will be implemented within the U.S. Geological Survey StreamStats Web-based geographic information system tool. StreamStats allows users to click on any ungaged site on a river and compute estimates of the eight selected statistics; in addition, 90-percent prediction intervals and the measured basin characteristics for the ungaged sites also are provided by the Web-based tool. StreamStats also allows users to click on any streamgage in Iowa and estimates computed for these eight selected statistics are provided for the streamgage.

Association of calcemia and serum vitamin D with 24H-urinary calcium excretion in a swiss population-based study

Background: Elevated urinary calcium excretion is associated with reduced bone mineral density. Population-based data on urinary calcium excretion are scarce. We explored the association of serum calcium and circulating levels of vitamin D (including 25(OH)D2 and 25(OH)D3) with urinary calcium excretion in men and women in a population-based study. Methods: We used data from the "Swiss Survey on Salt" conducted between 2010 and 2012 and including people aged 15 years and over. Twenty-four hour urine collection, blood analysis, clinical examination and anthropometric measures were collected in 11 centres from the 3 linguistic regions of Switzerland. Vitamin D was measured centrally using liquid chromatography - tandem mass spectrometry. Hypercalciuria was defined as urinary calcium excretion >0.1 mmol/kg/24h. Multivariable linear regression was used to explore factors associated with 24-hour urinary calcium excretion (mmol/24h) squared root transformed, taken as the dependant variable. Vitamin D was divided into monthspecific tertiles with the first tertile having the lowest value and the third tertile having the highest value. Results: The 669 men and 624 women had mean (SD) age of 49.2 (18.1) and 47 (17.9) years and a prevalence of hypercalciuria of 8.9% and 8.0%, respectively. In adjusted models, the association of urinary calcium excretion with protein-corrected serum calcium was (β coefficient } standard error, according to urinary calcium squared root transformed) 1.125 } 0.184 mmol/L per square-root (mmol/24h) (P<0.001) in women and 0.374 } 0.224 (P=0.096) in men. Men in the third month-specific vitamin D tertile had higher urinary calcium excretion than men in the first tertile (0.170 } 0.05 nmol/L per mmol/24h, P=0.001) and the corresponding association was 0.048 } 0.043, P= 0.272 in women. Conclusion: About one in eleven person has hypercalciuria in the Swiss population. The positive association of serum calcium with urinary calcium excretion was steeper in women than in men, independently of menopausal status. Circulating vitamin D was associated positively with urinary calcium excretion only in men. The reasons underlying the observed sex differences in the hormonal control of urinary calcium excretion need to be explored in further studies.

Artificially Intelligent and Adaptive Methods for Prediction and Analysis of Superheater Fireside Corrosion in Fluidized Bed Boilers

Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.

Plasma homocysteine and vitamin B12 serum levels, red blood cell folate concentrations, C677T methylenetetrahydrofolate reductase gene mutation and risk of recurrent miscarriage: a case-control study in Spain.

Background: Hyperhomocysteinemia and methylenetetrahydrofolate reductase (MTHFR) gene mutation have been postulated as a possible cause of recurrent miscarriage (RM). There is a wide variation in the prevalence of MTHFR polymorphisms and homocysteine (Hcy) plasma levels among populations around the world. The present study was undertaken to investigate the possible association between hyperhomocysteinemia and its causative genetic or acquired factors and RM in Catalonia, a Mediterranean region in Spain. Methods: Sixty consecutive patients with ≥ 3 unexplained RM and 30 healthy control women having at least one child but no previous miscarriage were included. Plasma Hcy levels, MTHFR gene mutation, red blood cell (RBC) folate and vitamin B12 serum levels were measured in all subjects. Results: No significant differences were observed neither in plasma Hcy levels, RBC folate and vitamin B12 serum levels nor in the prevalence of homozygous and heterozygous MTHFR gene mutation between the two groups studied. Conclusions: In the present study RM is not associated with hyperhomocysteinemia, and/or the MTHFR gene mutation.

Application of Neural Network Methods in the Prediction of Stock Markets

The purpose of the research is to define practical profit which can be achieved using neural network methods as a prediction instrument. The thesis investigates the ability of neural networks to forecast future events. This capability is checked on the example of price prediction during intraday trading on stock market. The executed experiments show predictions of average 1, 2, 5 and 10 minutes’ prices based on data of one day and made by two different types of forecasting systems. These systems are based on the recurrent neural networks and back propagation neural nets. The precision of the predictions is controlled by the absolute error and the error of market direction. The economical effectiveness is estimated by a special trading system. In conclusion, the best structures of neural nets are tested with data of 31 days’ interval. The best results of the average percent of profit from one transaction (buying + selling) are 0.06668654, 0.188299453, 0.349854787 and 0.453178626, they were achieved for prediction periods 1, 2, 5 and 10 minutes. The investigation can be interesting for the investors who have access to a fast information channel with a possibility of every-minute data refreshment.

Prédiction des complications après duodénopancréatectomie céphalique: validation d'un score de complications postopératoires = Prediction of complications after pancreaticoduodenectomy: validation of a postoperative complication score

Objectifs La chirurgie pancréatique reste associée à une morbidité postopératoire importante. Les efforts sont concentrés la plupart du temps sur la diminution de cette morbidité, mais la détection précoce de patients à risque de complications pourrait être une autre stratégie valable. Un score simple de prédiction des complications après duodénopancréatectomie céphalique a récemment été publié par Braga et al. La présente étude a pour but de valider ce score et de discuter de ses possibles implications cliniques. Méthodes De 2000 à 2015, 245 patients ont bénéficié d'une duodénopancréatectomie céphalique dans notre service. Les complications postopératoires ont été recensées selon la classification de Dindo et Clavien. Le score de Braga se base sur quatre paramètres : le score ASA (American Society of Anesthesiologists), la texture du pancréas, le diamètre du canal de Wirsung (canal pancréatique principal) et les pertes sanguines intra-opératoires. Un score de risque global de 0 à 15 peut être calculé pour chaque patient. La puissance de discrimination du score a été calculée en utilisant une courbe ROC (receiver operating characteristic). Résultats Des complications majeures sont apparues chez 31% des patients, alors que 17% des patients ont eu des complications majeures dans l'article de Braga. La texture du pancréas et les pertes sanguines étaient statistiquement significativement corrélées à une morbidité accrue. Les aires sous la courbe étaient respectivement de 0.95 et 0.99 pour les scores classés en quatre catégories de risques (de 0 à 3, 4 à 7, 8 à 11 et 12 à 15) et pour les scores individuels (de 0 à 15). Conclusions Le score de Braga permet donc une bonne discrimination entre les complications mineures et majeures. Notre étude de validation suggère que ce score peut être utilisé comme un outil pronostique de complications majeures après duodénopancréatectomie céphalique. Les implications cliniques, c'est-à-dire si les stratégies de prise en charge postopératoire doivent être adaptées en fonction du risque individuel du patient, restent cependant à élucider. -- Objectives Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. Methods From 2000 to 2012, 245 patients underwent pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (from 0 to 15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. Results Major complications occurred in 31% of patients compared to 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. The areas under curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. Conclusions The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, i.e., whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.

Prediction of Complications After Pancreaticoduodenectomy: Validation of a Postoperative Complication Score.

OBJECTIVES: Pancreatic surgery remains associated with important morbidity. Efforts are most commonly concentrated on decreasing postoperative morbidity, but early detection of patients at risk could be another valuable strategy. A simple prognostic score has recently been published. This study aimed to validate this score and discuss possible clinical implications. METHODS: From 2000 to 2012, 245 patients underwent a pancreaticoduodenectomy. Complications were graded according to the Dindo-Clavien Classification. The Braga score is based on American Society of Anesthesiologists score, pancreatic texture, Wirsung duct diameter, and blood loss. An overall risk score (0-15) can be calculated for each patient. Score discriminant power was calculated using a receiver operating characteristic curve. RESULTS: Major complications occurred in 31% of patients compared with 17% in Braga's data. Pancreatic texture and blood loss were independently statistically significant for increased morbidity. Areas under the curve were 0.95 and 0.99 for 4-risk categories and for individual scores, respectively. CONCLUSIONS: The Braga score discriminates well between minor and major complications. Our validation suggests that it can be used as a prognostic tool for major complications after pancreaticoduodenectomy. The clinical implications, that is, whether postoperative treatment strategies should be adapted according to the patient's individual risk, remain to be elucidated.

Conventional and novel cardiovascular risk factors in young Finns and their associations with structural and functional vascular changes of subclinical atherosclerosis. The Cardiovascular Risk in Young Finns Study

Background: Atherosclerosis begins in early life progressing from asymptomatic to symptomatic as we age. Although substantial progress has been made in identifying the determinants of atherosclerosis in middle to older age adults at increased cardiovascular risk, there is lack of data examining determinants and prediction of atherosclerosis in young adults. Aims: The current study was designed to investigate levels of cardiovascular risk factors in young adults, subclinical measures of atherosclerosis, and prediction of subclinical arterial changes with conventional risk factor measures and novel metabolic profiling of serum samples. Subjects and Methods: This thesis utilised data from the follow-ups performed in 2001 and 2007 in the Cardiovascular Risk in Young Finns study, a Finnish population-based prospective cohort study that examined 2,204 subjects who were aged 30-45 years in 2007. Subclinical atherosclerosis was studied using noninvasive ultrasound measurements of carotid intima-media thickness (IMT), carotid arterial distensibility (CDist) and brachial flow-mediated dilation (FMD). Measurements included conventional risk factors and metabolic profiling using highthroughput nuclear magnetic resonance (NMR) methods that provided data on 42 lipid markers and 16 circulating metabolites. Results: Trends in lipids were favourable between 2001 and 2007, whereas waist circumference, fasting glucose, and blood pressure levels increased. To study the stability of noninvasive ultrasound markers, 6-year tracking (the likelihood to maintain the original fractile over time) in 6 years was examined. IMT tracked more strongly than CDist and FMD. Cardiovascular risk scores (Framingham, SCORE, Finrisk, Reynolds and PROCAM) predicted subclinical atherosclerosis equally. Lipoprotein subclass testing did not improve the prediction of subclinical atherosclerosis over and above conventional risk factors. However, circulating metabolites improved risk stratification. Tyrosine and docosahexaenoic acid were found to be novel biomarkers of high IMT. Conclusions: Prediction of cardiovascular risk in young Finnish adults can be performed with any of the existing risk scores. The addition of metabonomics to risk stratification improves prediction of subclinical changes and enables more accurate targeting of prevention at an early stage.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.