281 Comparative Analysis of Risks Factors for Kidney Allograft Loss Due to BK Nephropathy and Graft Loss Due to Other Causes: UNOS Data Set

2020 ◽  
Vol 75 (4) ◽  
pp. 617-618
Keyword(s):  
Comparative Analysis ◽  
Graft Loss ◽  
Data Set ◽  
Kidney Allograft ◽  
Risks Factors ◽  
Allograft Loss

Factors that Influence the Durability of Transplanted Kidneys in South Africa

2019 ◽  
Vol 21 (2) ◽  
Author(s):  
Hillary Ndemera ◽  
Busisiwe R. Bhengu
Keyword(s):  
South Africa ◽  
Kidney Transplant ◽  
Lifestyle Modification ◽  
P Value ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Kidney Allograft ◽  
Factors Influencing ◽  
Allograft Loss ◽  
Transplanted Kidneys

Kidney transplantation is the cornerstone for renal treatment in patients with end-stage renal failure. Despite improvements in short-term outcomes of renal transplantation, kidney allograft loss remains a huge challenge. The aim of the study was to assess factors influencing the durability of transplanted kidneys among transplant recipients in South Africa. A descriptive cross-sectional study design was used. A random sampling was used to select 171 participants. Data were collected through structured face-to-face interviews developed from in-depth consideration of relevant literature. Data were coded and entered into the SPSS software, version 24. The entered data were analysed using descriptive and inferential statistics. The results revealed that the average durability of transplanted kidneys was 9.07 years among selected kidney transplant recipients in South Africa. Factors associated with the durability of transplanted kidneys included age, the sewerage system and strict immunosuppressive adherence, all with a P-value = .000, followed by the mode of transport (P-value = .001) and support system (P-value = .004). Other variables including demographics, the healthcare system, medication and lifestyle modification engagement were not associated with the durability of transplanted kidneys. Understanding the factors influencing the durability of transplanted kidneys among kidney transplant recipients in South Africa is crucial. The study revealed associated factors and gaps which may be contributory factors to kidney allograft loss. This study provides an opportunity to introduce specific interventions to nephrology professionals to promote prolonged graft durability. It is recommended that a specific intervention model be developed, which targets South African kidney recipients taking into account the significant variables in this study and the socio-economic status of the country.

The Structural Landscape of SARS-CoV-2 Main Protease: Hints for Inhibitor Search.

2020 ◽  
Author(s):  
Luigi Leonardo Palese
Keyword(s):  
Comparative Analysis ◽  
Global Health ◽  
Binding Site ◽  
Causative Agent ◽  
Data Set ◽  
Substrate Binding Site ◽  
Global Pandemic ◽  
Main Protease ◽  
Crystallographic Structures ◽  
Structural Aspects

In 2019, an outbreak occurred which resulted in a global pandemic. The causative agent of this serious global health threat was a coronavirus similar to the agent of SARS, referred to as SARS-CoV-2. In this work an analysis of the available structures of the SARS-CoV-2 main protease has been performed. From a data set of crystallographic structures the dynamics of the protease has been obtained. Furthermore, a comparative analysis of the structures of SARS-CoV-2 with those of the main protease of the coronavirus responsible of SARS (SARS-CoV) was carried out. The results of these studies suggest that, although main proteases of SARS-CoV and SARS-CoV-2 are similar at the backbone level, some plasticity at the substrate binding site can be observed. The consequences of these structural aspects on the search for effective inhibitors of these enzymes are discussed, with a focus on already known compounds. The results obtained show that compounds containing an oxirane ring could be considered as inhibitors of the main protease of SARS-CoV-2.

Comparative Analysis of Machine Learning Techniques Using Predictive Modeling

2020 ◽  
Vol 13 ◽  
Author(s):  
Ritu Khandelwal ◽  
Hemlata Goyal ◽  
Rajveer Singh Shekhawat
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Data Science ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Future Trends ◽  
Data Set ◽  
Learning Stage ◽  
Learning Techniques ◽  
Different Types

Introduction: Machine learning is an intelligent technology that works as a bridge between businesses and data science. With the involvement of data science, the business goal focuses on findings to get valuable insights on available data. The large part of Indian Cinema is Bollywood which is a multi-million dollar industry. This paper attempts to predict whether the upcoming Bollywood Movie would be Blockbuster, Superhit, Hit, Average or Flop. For this Machine Learning techniques (classification and prediction) will be applied. To make classifier or prediction model first step is the learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations. Methods: All the techniques related to classification and Prediction such as Support Vector Machine(SVM), Random Forest, Decision Tree, Naïve Bayes, Logistic Regression, Adaboost, and KNN will be applied and try to find out efficient and effective results. All these functionalities can be applied with GUI Based workflows available with various categories such as data, Visualize, Model, and Evaluate. Result: To make classifier or prediction model first step is learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations Conclusion: This paper focuses on Comparative Analysis that would be performed based on different parameters such as Accuracy, Confusion Matrix to identify the best possible model for predicting the movie Success. By using Advertisement Propaganda, they can plan for the best time to release the movie according to the predicted success rate to gain higher benefits. Discussion: Data Mining is the process of discovering different patterns from large data sets and from that various relationships are also discovered to solve various problems that come in business and helps to predict the forthcoming trends. This Prediction can help Production Houses for Advertisement Propaganda and also they can plan their costs and by assuring these factors they can make the movie more profitable.

Intuitionistic fuzzy two-factor variance analysis of movie ticket sales

2021 ◽  
pp. 1-11
Author(s):  
Velichka Traneva ◽  
Stoyan Tranev
Keyword(s):  
Comparative Analysis ◽  
Real Data ◽  
Intuitionistic Fuzzy Sets ◽  
Real Numbers ◽  
Data Set ◽  
Important Method ◽  
Ticket Sales ◽  
Intuitionistic Fuzzy ◽  
The One ◽  
First Time

Analysis of variance (ANOVA) is an important method in data analysis, which was developed by Fisher. There are situations when there is impreciseness in data In order to analyze such data, the aim of this paper is to introduce for the first time an intuitionistic fuzzy two-factor ANOVA (2-D IFANOVA) without replication as an extension of the classical ANOVA and the one-way IFANOVA for a case where the data are intuitionistic fuzzy rather than real numbers. The proposed approach employs the apparatus of intuitionistic fuzzy sets (IFSs) and index matrices (IMs). The paper also analyzes a unique set of data on daily ticket sales for a year in a multiplex of Cinema City Bulgaria, part of Cineworld PLC Group, applying the two-factor ANOVA and the proposed 2-D IFANOVA to study the influence of “ season ” and “ ticket price ” factors. A comparative analysis of the results, obtained after the application of ANOVA and 2-D IFANOVA over the real data set, is also presented.

Patient outcomes after kidney allograft loss

2008 ◽  
Vol 22 (1) ◽  
pp. 62-72 ◽  
Author(s):  
Roberto Marcén ◽  
José Luis Teruel
Keyword(s):  
Patient Outcomes ◽  
Kidney Allograft ◽  
Allograft Loss

The use of MSR (Minimum Sample Richness) for sample assemblage comparisons

Paleobiology ◽  
2011 ◽  
Vol 37 (4) ◽  
pp. 696-709 ◽  
Author(s):  
Kenny J. Travouillon ◽  
Gilles Escarguel ◽  
Serge Legendre ◽  
Michael Archer ◽  
Suzanne J. Hand
Keyword(s):  
Comparative Analysis ◽  
Classification Accuracy ◽  
Data Set ◽  
Massif Central ◽  
Taxonomic Analysis ◽  
Early Neogene ◽  
Fossil Assemblages ◽  
Minimum Sample

Minimum Sample Richness (MSR) is defined as the smallest number of taxa that must be recorded in a sample to achieve a given level of inter-assemblage classification accuracy. MSR is calculated from known or estimated richness and taxonomic similarity. Here we test MSR for strengths and weaknesses by using 167 published mammalian local faunas from the Paleogene and early Neogene of the Quercy and Limagne area (Massif Central, southwestern France), and then apply MSR to 84 Oligo-Miocene faunas from Riversleigh, northwestern Queensland, Australia. In many cases, MSR is able to detect the assemblages in the data set that are potentially too incomplete to be used in a similarity-based comparative taxonomic analysis. The results show that the use of MSR significantly improves the quality of the clustering of fossil assemblages. We conclude that this method can screen sample assemblages that are not representative of their underlying original living communities. Ultimately, it can be used to identify which assemblages require further sampling before being included in a comparative analysis.

scholarly journals P1706THE GRAFT SURVIVAL OF KIDNEY TRANSPLANTATION ACCORDING TO ETHNICITY IN KIDNEY TRANSPLANT RECIPIENTS

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Yeonsoon Jung ◽  
Jisu Kim ◽  
Haesu Jeon ◽  
Ye Na Kim ◽  
Ho Sik Shin ◽  
...  
Keyword(s):  
African American ◽  
Kidney Transplantation ◽  
Kidney Transplant ◽  
Graft Survival ◽  
Cox Regression ◽  
Patient Survival ◽  
Graft Loss ◽  
Transplant Recipients ◽  
Kidney Transplant Recipients ◽  
Data Set

Abstract Background African American kidney transplant recipients experience disproportionately high rates of graft loss. The aim of this analysis was to use a UNOS data set that contains detailed baseline and longitudinal clinical data to establish and quantify the impact of the current overall graft loss definition on suppressing the true disparity magnitude in US AA kidney transplant outcomes. Methods Longitudinal cohort study of kidney transplant recipients using a data set created by United Network for Organ Sharing (UNOS), including 266,128 (African American 70,215, Non-African American 195,913) transplant patient between 1987 and December 2016. Multivariable analysis was conducted using 2-stage joint modeling of random and fixed effects of longitudinal data (linear mixed model) with time to event outcomes (Cox regression). Results 195,913 non-African American (AA) (73.6%) were compared with 70,215 AA (26.4%) recipients. 10-year-graft survival of AA in all era is lower than that of non-AA (31% in deceased kidney transplants (DKT) AA recipient and 42% in living kidney transplantation (LKT) non-AA recipient). 10-year-patient survival of AA with functioning graft in all era is similar that of non-AA. Multivariate Cox regression of factors associated with patient survival with functioning graft are acute rejection within 6 months, DM, hypertension and etc. Pre-transplant recipient BMI in AA show the trend as a protective factor in patient survival with functioning graft although not significantly in statistics Conclusions African American kidney transplant recipients experience a substantial disparity in graft loss, but not patient death with functioning graft.

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