274 research outputs found

    A Long Duration Orbital Simulator (LDOS) Utilized in Technical Planning Activities

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    This paper describes the development and use of a long duration orbital simulator (LDOS). The LDOS capabilities, options, accuracy, and central processing unit (CPU) usage are discussed. The applications described using the LDOS are associated with (a) Manned Space Flight Network (MSFN) support of long duration missions, (b) environmental effects on high earth orbits and (c) long term orbit decay. The appendix depicts the salient portions of the math model

    Improving CT prediction of treatment response in patients with metastatic colorectal carcinoma using statistical learning theory

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    Abstract Background Significant interest exists in establishing radiologic imaging as a valid biomarker for assessing the response of cancer to a variety of treatments. To address this problem, we have chosen to study patients with metastatic colorectal carcinoma to learn whether statistical learning theory can improve the performance of radiologists using CT in predicting patient treatment response to therapy compared with the more traditional RECIST (Response Evaluation Criteria in Solid Tumors) standard. Results Predictions of survival after 8 months in 38 patients with metastatic colorectal carcinoma using the Support Vector Machine (SVM) technique improved 30% when using additional information compared to WHO (World Health Organization) or RECIST measurements alone. With both Logistic Regression (LR) and SVM, there was no significant difference in performance between WHO and RECIST. The SVM and LR techniques also demonstrated that one radiologist consistently outperformed another. Conclusions This preliminary research study has demonstrated that SLT algorithms, properly used in a clinical setting, have the potential to address questions and criticisms associated with both RECIST and WHO scoring methods. We also propose that tumor heterogeneity, shape, etc. obtained from CT and/or MRI scans be added to the SLT feature vector for processing

    Clinical Decision Support System (CDSS) for the Classification of Atypical Cells in Pleural Effusions

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    AbstractThe objective of this research is to develop a prototype Clinical Decision Support System (CDSS) to aid pathologists in correctly discriminating between reactive mesothelial cells and malignant epithelial cells. Currently, there is great difficulty in visually discriminating between cells that are malignant and cells that are otherwise reactive to antigens present in the effusion. Features have been identified, which can correctly discriminate between benign epithelial cells and malignant epithelial cells with a validation AZ accuracy of ∼ 0.934, training AZ of ∼ 0.937. Using these features, the system trained on visually known cases was shown to find discriminating information in the feature subset of the atypical cases by examining probabilities generated from subjecting the system to atypical cells. While these results are preliminary, they do demonstrate that an intelligent CDSS, which has the potential to discriminate between reactive mesothelial cells and malignant epithelial cells, designed using newly developed and/or revised statistical learning theory (SLT) algorithms, has the potential to be used as a second opinion diagnostic aid by physicians, as they deem appropriate

    Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data

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    <p>Abstract</p> <p>Background</p> <p>Statistical learning (SL) techniques can address non-linear relationships and small datasets but do not provide an output that has an epidemiologic interpretation.</p> <p>Methods</p> <p>A small set of clinical variables (CVs) for stage-1 non-small cell lung cancer patients was used to evaluate an approach for using SL methods as a preprocessing step for survival analysis. A stochastic method of training a probabilistic neural network (PNN) was used with differential evolution (DE) optimization. Survival scores were derived stochastically by combining CVs with the PNN. Patients (n = 151) were dichotomized into favorable (n = 92) and unfavorable (n = 59) survival outcome groups. These PNN derived scores were used with logistic regression (LR) modeling to predict favorable survival outcome and were integrated into the survival analysis (i.e. Kaplan-Meier analysis and Cox regression). The hybrid modeling was compared with the respective modeling using raw CVs. The area under the receiver operating characteristic curve (Az) was used to compare model predictive capability. Odds ratios (ORs) and hazard ratios (HRs) were used to compare disease associations with 95% confidence intervals (CIs).</p> <p>Results</p> <p>The LR model with the best predictive capability gave Az = 0.703. While controlling for gender and tumor grade, the OR = 0.63 (CI: 0.43, 0.91) per standard deviation (SD) increase in age indicates increasing age confers unfavorable outcome. The hybrid LR model gave Az = 0.778 by combining age and tumor grade with the PNN and controlling for gender. The PNN score and age translate inversely with respect to risk. The OR = 0.27 (CI: 0.14, 0.53) per SD increase in PNN score indicates those patients with decreased score confer unfavorable outcome. The tumor grade adjusted hazard for patients above the median age compared with those below the median was HR = 1.78 (CI: 1.06, 3.02), whereas the hazard for those patients below the median PNN score compared to those above the median was HR = 4.0 (CI: 2.13, 7.14).</p> <p>Conclusion</p> <p>We have provided preliminary evidence showing that the SL preprocessing may provide benefits in comparison with accepted approaches. The work will require further evaluation with varying datasets to confirm these findings.</p

    Quality of life in Type 1 (insulin-dependent) diabetic patients prior to and after pancreas and kidney transplantation in relation to organ function

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    Improvement of the quality of life in Type 1 (insulin-dependent) diabetic patients with severe late complications is one of the main goals of pancreas and/or kidney grafting. To assess the influences of these treatment modalities on the different aspects of the quality of life a cross-sectional study in 157 patients was conducted. They were categorized into patients pre-transplant without dialysis (n=29; Group A), pre-transplant under dialysis (n=44; Group B), post-transplant with pancreas and kidney functioning (n=31; Group C), post-transplant with functioning kidney, but insulin therapy (n=29; Group D), post-transplant under dialysis and insulin therapy again (n=15; Group E) and patients after single pancreas transplantation and rejection, with good renal function, but insulin therapy (n=9; Group F). All patients answered a mailed, self-administered questionnaire (217 questions) consisting of a broad spectrum of rehabilitation criteria. The results indicate a better quality of life in Groups C and D as compared to the other groups. In general the scores are highest in C, but without any significant difference to D. Impressive significant differences between C or D and the other groups were found especially in their satisfaction with physical capacity, leisure-time activities or the overall quality of life. The satisfaction with the latter is highest in C (mean±SEM: 4.0±0.2 on a 1 to 5-rating scale; significantly different from A: 3.1±0.1, B: 2.7±0.2 and E: 2.6±0.3; p<0.01), followed by D (3.8±0.2; significantly different from B and E; p<0.01). Group F shows a mean of 3.1±0.4, which is not significantly different from C. The percentages of patients in each group, who are not working: A: 38 %, B: 64 %, C: 74 %, D: 66 %, E: 87 % and F: 78 % indicate that there is no marked improvement in the vocational situation after successful grafting

    Assessing institutional relations in development partnerships: the Land Development Corporation and the Hong Kong Government prior to 1997

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    This paper interprets and develops contemporary notions of partnership in relation to Hong Kong's Land Development Corporation. It demonstrates how such agencies are likely to become overdependent on their private-sector partners or ineffective in policy delivery, unless endowed with adequate powers and resources. In this context, it suggests that the LDC's capacity to promote urban renewal was undermined particularly by the institutional requirement to assemble redevelopment sites in multiple ownership principally through negotiation. While seeking to explain this weakness in relation to the socio-cultural context of Hong Kong, it warns that, in applying the Western experience of partnership elsewhere, full account must be taken of local circumstances and constraints
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