1,064,736 research outputs found

    A decision framework for product global outsourcing in small and medium-sized companies.

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    This research will focus on small and medium-sized companies. A decision framework of Product Global Outsourcing (PGO) will be presented. This framework integrates and links the elements that could have impacts on product global outsourcing decision-making, and systematically analyzes the decision-making process step by step. The objective of this framework is to present a simplified and reified approach of PGO decision-making for small and medium-sized companies. The framework is organized in five main levels: (1) environment analysis - the identification of the actual situations surrounding and impacting upon the company, including the external and internal environment; (2) total cost analysis - a total cost mathematical model will be developed; (3) objective analysis - setup the product global outsourcing goals from five aspects; (4) strategy and business planning analysis - identify the company\u27s strategy to achieve its objectives, and provide the business planning, such as supplier selection, contract negotiation and project execution management; and (5) risk analysis. (Abstract shortened by UMI.)Dept. of Industrial and Manufacturing Systems Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .M46. Source: Masters Abstracts International, Volume: 44-03, page: 1476. Thesis (M.A.Sc.)--University of Windsor (Canada), 2005

    A qualitative comparison of how older breast cancer survivors process treatment information regarding endocrine therapy.

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    BACKGROUND:It remains unclear how information about aromatase inhibitors (AI) impacts women's decision-making about persistence with endocrine therapy. PURPOSE:To describe and compare how women treated for primary early stage breast cancer either persisting or not persisting with an AI received, interpreted, and acted upon AI-related information. DESIGN:Thematic analysis was used to sort and compare the data into the most salient themes. PARTICIPANTS:Women (N = 54; 27 persisting, 27 not persisting with an AI) aged 65-93 years took part in qualitative interviews. RESULTS:Women in both subgroups described information similarly in terms of its value, volume, type, and source. Aspects of AI-related information that either differed between the subgroups or were misunderstood by one or both subgroups included: (1) knowledge of AI or tamoxifen prior to cancer diagnosis, (2) use of online resources, (3) misconceptions about estrogen, hormone replacement therapies and AI-related symptoms, and (4) risk perception and the meaning and use of recurrence statistics such as Oncotype DX. CONCLUSIONS:Persisters and nonpersisters were similar in their desire for more information about potential side effects and symptom management at AI prescription and subsequent appointments. Differences included how information was obtained and interpreted. Interactive discussion questions are shared that can incorporate these findings into clinical settings

    Predicting low-risk prostate cancer from transperineal saturation biopsies

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    Introduction: To assess the performance of five previously described clinicopathological definitions of low-risk prostate cancer (PC). Materials and Methods: Men who underwent radical prostatectomy (RP) for clinical stage ≤T2, PSA \u3c10 ng/mL, Gleason score \u3c8 PC, diagnosed by transperineal template-guided saturation biopsy were included. The performance of five previously described criteria (i.e., criteria 1–5, criterion 1 stringent (Gleason score 6 + ≤5mm total max core length PC + ≤3mm max per core length PC) up to criterion 5 less stringent (Gleason score 6-7 with ≤5% Gleason grade 4) was analysed to assess ability of each to predict insignificant disease in RP specimens (defined as Gleason score ≤6 and total tumour volume \u3c2.5mL, or Gleason score 7 with ≤5% grade 4 and total tumour volume \u3c0.7 mL). Results: 994 men who underwent RP were included. Criterion 4 (Gleason score 6) performed best with area under the curve of receiver operating characteristics 0.792. At decision curve analysis, criterion 4 was deemed clinically the best performing transperineal saturation biopsy-based definition for low-risk PC. Conclusions: Gleason score 6 disease demonstrated a superior trade-off between sensitivity and specificity for clarifying low-risk PC that can guide treatment and be used as reference test in diagnostic studies. prostate cancer screening (PSA), testing practices, United Kingdom, Australia, qualitative stud

    Adjuvant vs. salvage radiation therapy in men with high-risk features after radical prostatectomy: Survey of North American genitourinary expert radiation oncologists

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    INTRODUCTION: The management of patients with high-risk features after radical prostatectomy (RP) is controversial. Level 1 evidence demonstrates that adjuvant radiation therapy (RT) improves survival compared to no treatment; however, it may overtreat up to 30% of patients, as randomized clinical trials (RCTs) using salvage RT on observation arms failed to reveal a survival advantage of adjuvant RT. We, therefore, sought to determine the current view of adjuvant vs. salvage RT among North American genitourinary (GU) radiation oncology experts. METHODS: A survey was distributed to 88 practicing North American GU physicians serving on decision-making committees of cooperative group research organizations. Questions pertained to opinions regarding adjuvant vs. salvage RT for this patient population. Treatment recommendations were correlated with practice patterns using Fisher's exact test. RESULTS: Forty-two of 88 radiation oncologists completed the survey; 23 (54.8%) recommended adjuvant RT and 19 (45.2%) recommended salvage RT. Recommendation of active surveillance for Gleason 3+4 disease was a significant predictor of salvage RT recommendation (p=0.034), and monthly patient volume approached significance for recommendation of adjuvant over salvage RT; those seeing <15 patients/month trended towards recommending adjuvant over salvage RT (p=0.062). No other demographic factors approached significance. CONCLUSIONS: There is dramatic polarization among North American GU experts regarding optimal management of patients with high-risk features after RP. Ongoing RCTs will determine whether adjuvant RT improves survival over salvage RT. Until then, the almost 50/50 division seen from this analysis should encourage practicing clinicians to discuss the ambiguity with their patients

    Detecting the Psychosis Prodrome Across High-Risk Populations Using Neuroanatomical Biomarkers

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    To date, the MRI-based individualized prediction of psychosis has only been demonstrated in single-site studies. It remains unclear if MRI biomarkers generalize across different centers and MR scanners and represent accurate surrogates of the risk for developing this devastating illness. Therefore, we assessed whether a MRI-based prediction system identified patients with a later disease transition among 73 clinically defined high-risk persons recruited at two different early recognition centers. Prognostic performance was measured using cross-validation, independent test validation, and Kaplan-Meier survival analysis. Transition outcomes were correctly predicted in 80% of test cases (sensitivity: 76%, specificity: 85%, positive likelihood ratio: 5.1). Thus, given a 54-month transition risk of 45% across both centers, MRI-based predictors provided a 36%-increase of prognostic certainty. After stratifying individuals into low-, intermediate-, and high-risk groups using the predictor's decision score, the high- vs low-risk groups had median psychosis-free survival times of 5 vs 51 months and transition rates of 88% vs 8%. The predictor's decision function involved gray matter volume alterations in prefrontal, perisylvian, and subcortical structures. Our results support the existence of a cross-center neuroanatomical signature of emerging psychosis enabling individualized risk staging across different high-risk populations. Supplementary results revealed that (1) potentially confounding between-site differences were effectively mitigated using statistical correction methods, and (2) the detection of the prodromal signature considerably depended on the available sample sizes. These observations pave the way for future multicenter studies, which may ultimately facilitate the neurobiological refinement of risk criteria and personalized preventive therapies based on individualized risk profiling tool

    The role of clinicians in determining radioactive iodine use for low‐risk thyroid cancer

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    BACKGROUND: There is controversy regarding the optimal management of thyroid cancer. The proportion of patients with low‐risk thyroid cancer who received radioactive iodine (RAI) treatment increased over the last 20 years, and little is known about the role played by clinicians in hospital‐level RAI use for low‐risk disease. METHODS: Thyroid surgeons affiliated with 368 hospitals that had Commission on Cancer‐accredited cancer programs were surveyed. Survey data were linked to data reported to the National Cancer Database. A multivariable analysis was used to assess the relation between clinician decision makers and hospital‐level RAI use after total thyroidectomy in patients with stage I, well differentiated thyroid cancer. RESULTS: The survey response rate was 70% (560 of 804 surgeons). The surgeon was identified as the primary decision maker by 16% of the surgeons; the endocrinologist was identified as the primary decision maker by 69%, and a nuclear medicine, radiologist, or other physician was identified as the primary decision maker by 15%. In a multivariable analysis controlling for hospital case volume and hospital type, when the primary decision maker was in a specialty other than endocrinology or surgery, there was greater use of RAI at the hospital ( P < .001). A greater number of providers at the hospital where RAI was administered and having access to a tumor board also were associated with increased use of RAI ( P < .001 and P = .006, respectively). CONCLUSIONS: The specialty of the primary decision maker, the number of providers administering RAI, and having access to a tumor board were associated significantly with the use of RAI for stage I thyroid cancer. The findings have implications for addressing nonclinical variation between hospitals, with a marked heterogeneity in decision making suggesting that standardization of care will be challenging. Cancer 2013. © 2012 American Cancer Society. There is heterogeneity in clinician decision making for the management of patients with thyroid cancer. The specialty of the primary decision maker, the number of providers administering radioactive iodine, and access to a tumor board are associated significantly with the use of radioactive iodine for stage I thyroid cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96331/1/27721_ftp.pd

    A predictive model for kidney transplant graft survival using machine learning

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    Kidney transplantation is the best treatment for end-stage renal failure patients. The predominant method used for kidney quality assessment is the Cox regression-based, kidney donor risk index. A machine learning method may provide improved prediction of transplant outcomes and help decision-making. A popular tree-based machine learning method, random forest, was trained and evaluated with the same data originally used to develop the risk index (70,242 observations from 1995-2005). The random forest successfully predicted an additional 2,148 transplants than the risk index with equal type II error rates of 10%. Predicted results were analyzed with follow-up survival outcomes up to 240 months after transplant using Kaplan-Meier analysis and confirmed that the random forest performed significantly better than the risk index (p<0.05). The random forest predicted significantly more successful and longer-surviving transplants than the risk index. Random forests and other machine learning models may improve transplant decisions.Comment: This work has been published: Pahl ES, Street WN, Johnson HJ, Reed AI. "A Predictive Model for Kidney Transplant Graft Survival Using Machine Learning." 4th International Conference on Computer Science and Information Technology (COMIT 2020), November 28-29, 2020, Dubai, UAE. ISBN: 978-1-925953-30-5. Volume 10, Number 16.10.5121/csit.2020.10160

    Analisis Faktor Penentu Kompensasi Eksekutif Dan Hubungan Kompensasi Eksekutif Dengan Kinerja Perusahaan

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    The objectives of this research were (1) to analyse determinants of the influencing factors of the Indonesian Estate State-owned enterprises\u27 executive compensations; and (2) to analyse the relationship between compensation executive and firm performances. Statistical methods used for analysing these objectives were Structural Equation Model (SEM), contingency analysis, regresion analysis and qualitative analysis. The study found out that from all identified variables, executive decision mechanism, job complexity, firm size, firm ability to pay compensation, and product diversification and market expansionhad positive correlation and significant influenced to executive compensation. Human capital, business risk, executive employment market had significant correlations to executive compensation. The research had also shown a result that executive compensation provide positive correlation and significant influence towards financial performance (EBIT), customer performance (sales volume, output price, market area), internal process performance (OER target, OER realisation), and growth and learning performance (number of training investment, number of employees participated intraining). However, executive compensation did not give positive correlation and significant influenced towards financial performance (ROE) and customer performance(market share). This research also showed that direction of executive compensation was heading to company\u27s performance and not the opposite way

    Systems engineering and integration: Cost estimation and benefits analysis

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    Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required
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