Journal of biometrics & biostatistics最新文献_第2页

Improving the t-SNE Algorithms for Cytometry and Other Technologies: Cen-Se' Mapping 改进细胞术中的t-SNE算法及其他技术:cense - Mapping

Journal of biometrics & biostatistics Pub Date : 2019-05-20 DOI: 10.4172/2155-6180.1000430

C. B. Bagwell, C. Bray, D. Herbert, Beth L. Hill, M. Inokuma, Gregory T. Stelzer, B. Hunsberger

{"title":"Improving the t-SNE Algorithms for Cytometry and Other Technologies: Cen-Se' Mapping","authors":"C. B. Bagwell, C. Bray, D. Herbert, Beth L. Hill, M. Inokuma, Gregory T. Stelzer, B. Hunsberger","doi":"10.4172/2155-6180.1000430","DOIUrl":"https://doi.org/10.4172/2155-6180.1000430","url":null,"abstract":"SNE methods are a set of 9 to 10 interconnected algorithms that map high-dimensional data into low-dimensional space while minimizing loss of information. Each step in this process is important for producing high-quality maps. Cense′™ mapping not only enhances many of the steps in this process but also fundamentally changes the underlying mathematics to produce high-quality maps. The key mathematical enhancement is to leverage the Cauchy distribution for creating both high-dimensional and lowdimensional similarity matrices. This simple change eliminates the necessity of using perplexity and entropy and results in maps that optimally separate clusters defined in high-dimensional space. It also eliminates the loss of cluster resolution commonly seen with t-SNE with higher numbers of events. There is just one free parameter for Cen-se′ mapping, and that parameter rarely needs to change. Other enhancements include a relatively low memory footprint, highly threaded implementation, and a final classification step that can process millions of events in seconds. When the Cen-se′ mapping system is integrated with probability state modeling, the clusters of events are positioned in a reproducible manner and are colored, labeled, and enumerated automatically. We provide a step-by-step, simple example that describes how the Cen-se′ method works and differs from the t-SNE method. We present data from several experiments to compare the two mapping strategies on high-dimensional mass cytometry data. We provide a section on information theory to explain how the steepest gradient equations were formulated and how they control the movement of the low-dimensional points as the system renders the map Since existing implementations of the t-SNE algorithm can easily be modified with many of these enhancements, this work should result in more effective use of this very exciting and far-reaching new technology.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"10 1","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2019-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42397992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Prevalence of Social Isolation and Psychometric Properties of Lubben Social Network Scale among Older Diabetic Patients in Abeokuta, Nigeria 尼日利亚Abeokuta地区老年糖尿病患者的社会孤立程度及Lubben社会网络量表的心理测量特征

Journal of biometrics & biostatistics Pub Date : 2019-02-18 DOI: 10.4172/2155-6180.1000422

D. Ajay, Gbolahan Akanji Fabiyi, S. Bello

{"title":"Prevalence of Social Isolation and Psychometric Properties of Lubben Social Network Scale among Older Diabetic Patients in Abeokuta, Nigeria","authors":"D. Ajay, Gbolahan Akanji Fabiyi, S. Bello","doi":"10.4172/2155-6180.1000422","DOIUrl":"https://doi.org/10.4172/2155-6180.1000422","url":null,"abstract":"Introduction: Social isolation is a global public health challenge. Social isolation may worsen the prognosis of diabetes. Assessment of social isolation among older diabetic adults is important, and the use of valid and reliable measure is necessary. Therefore, the aim of this study was to determine the prevalence of social isolation, and to investigate the factor structure and reliability of the abbreviated version of Lubben Social Network Scale (LSNS-6) among older diabetic patients in Abeokuta, Nigeria. \u0000Methods: A descriptive cross-sectional study was conducted, wherein type 2 diabetic patients aged 50 and above were consecutively recruited from Federal Medical Centre, Idi Aba, and General Hospital, Ijaye. A pre-tested, intervieweradministered, structured questionnaire was used to collect data. The factor structure of the LSNS-6 was investigated using exploratory factor analysis (EFA) with principal axis factoring method of estimation and varimax rotation. Estimates of the internal consistency reliability of the subscales and the overall scale were obtained from alpha coefficients. \u0000 Results: A total of 160 respondents with the mean age of 63.2 ± 9.6 years and the mean duration of diabetes of 7.5 ± 6.8 years participated in the study. Sixty-six (41.3%) respondents were socially isolated (LSNS-6 score < 12). The EFA revealed 2 factors (i.e. Family and Friend) which explained 72.6% of the total variance. Cronbach’s alpha coefficients for Family and Friend subscales were 0.84 and 0.90, respectively. Stratified alpha for the scale was 0.90. \u0000Conclusion: The prevalence of social isolation among the older diabetic patients was high. Also, the LSNS-6 was found to be a reliable and valid instrument for assessing social isolation in this study population. Assessment and management of social isolation should be incorporated into diabetes treatment plan for older diabetic patients.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43598598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Assessment of Basic and Advanced Knowledge in Biostatistics and Clinical Research among Health care Professionals at King Fahad Medical City, Riyadh, KSA: A cross-Sectional Survey 沙特利雅得法赫德国王医疗城卫生保健专业人员生物统计学和临床研究基本知识和高级知识评估:一项横断面调查

Journal of biometrics & biostatistics Pub Date : 2019-01-01 DOI: 10.37421/JBMBS.2019.10.434

M. Bashir, Humariya Heena, T. Wani

{"title":"Assessment of Basic and Advanced Knowledge in Biostatistics and Clinical Research among Health care Professionals at King Fahad Medical City, Riyadh, KSA: A cross-Sectional Survey","authors":"M. Bashir, Humariya Heena, T. Wani","doi":"10.37421/JBMBS.2019.10.434","DOIUrl":"https://doi.org/10.37421/JBMBS.2019.10.434","url":null,"abstract":"Background: Adequate biostatistics knowledge among healthcare professionals is imperative for understanding medical literature and practicing evidence-based medicine. This study assessed the basic and advanced knowledge in biostatistics and clinical research among healthcare workers at the King Fahad Medical City (KFMC), Riyadh, Saudi Arabia. Methods: In this cross-sectional survey, data was collected from healthcare providers using a self-administered questionnaire, having questions related to demographics, biostatistics and clinical research. Data analysis was performed using statistical package SPSS 22. Results: Of 194 participants (63 [32.5%] consultants, 52 [26.8%] residents, and 79 [40.7%] allied healthcare providers), 45.4% had positive attitude towards learning biostatistics. Only 35.1% correctly answered biostatistics and clinical research instrument-related questions. Half participants had low score, 33% had good score, and 18-19% had excellent score of basic and advanced knowledge of biostatistics and clinical research. The highest degree and number of years of experience in biostatistics after medical school graduation were significantly (χ2 (2)=16.589, p<0.001) associated with basic and advanced biostatistics knowledge scores. Conclusion: Timely and painstaking training courses in biostatistics and clinical research are needed to improve the research standards in Saudi Arabia. Interested candidates should collaborated with statisticians to improve quality of their work and enhance their statistical skills.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"190 1","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70054254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Simple Power and Sample Size Estimation for Non-Randomized Longitudinal Difference in Differences Studies 差异研究中非随机纵向差异的简单幂和样本量估计

Journal of biometrics & biostatistics Pub Date : 2018-11-26 DOI: 10.4172/2155-6180.1000415

Yirui Hu, D. Hoover

{"title":"Simple Power and Sample Size Estimation for Non-Randomized Longitudinal Difference in Differences Studies","authors":"Yirui Hu, D. Hoover","doi":"10.4172/2155-6180.1000415","DOIUrl":"https://doi.org/10.4172/2155-6180.1000415","url":null,"abstract":"Intervention effects on continuous longitudinal normal outcomes are often estimated in two-arm pre-post interventional studies with b≥1 pre- and k≥1 post-intervention measures using “Difference-in-Differences” (DD) analysis. Although randomization is preferred, non-randomized designs are often necessary due to practical constraints. Power/sample size estimation methods for non-randomized DD designs that incorporate the correlation structure of repeated measures are needed. We derive Generalized Least Squares (GLS) variance estimate of the intervention effect. For the commonly assumed compound symmetry (CS) correlation structure (where the correlation between all repeated measures is a constantρ) this leads to simple power and sample size estimation formulas that can be implemented using pencil and paper. Given a constrained number of total timepoints (T), having as close to possible equal number of pre-and post-intervention timepoints (b=k) achieves greatest power. When planning a study with 7 or less timepoints, given large ρ(ρ≥0.6) in multiple baseline measures (b≥2) or ρ≥0.8 in a single baseline setting, the improvement in power from a randomized versus non-randomized DD design may be minor. Extensions to cluster study designs and incorporation of time invariant covariates are given. Applications to study planning are illustrated using three real examples with T=4 timepoints and ρ ranging from 0.55 to 0.75.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41917199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

The human hand and foot in evolution and art : the effects of wearing footwear 人类的手和脚在进化和艺术:穿鞋的影响

Journal of biometrics & biostatistics Pub Date : 2018-04-04 DOI: 10.4172/2155-6180.1000394

C. Qualls, Peter Evans, A. Perciaccante, R. Bianucci, D. Lippi, O. Appenzeller

引用次数: 0

Replacement of Directed Graph by Acyclic Directed Graph and Its Application in Biostatistics 无环有向图替代有向图及其在生物统计学中的应用

Journal of biometrics & biostatistics Pub Date : 2018-02-28 DOI: 10.4172/2155-6180.1000390

Tsitsiashvili Gurami, Bulgakov Victor, Losev Alexandr

引用次数: 2

A Brand New Approach to Sets in Mathematics 一种全新的数学集合方法

Journal of biometrics & biostatistics Pub Date : 2018-02-27 DOI: 10.4172/2155-6180.1000391

N. Demirkuş, Divin Alkan

{"title":"A Brand New Approach to Sets in Mathematics","authors":"N. Demirkuş, Divin Alkan","doi":"10.4172/2155-6180.1000391","DOIUrl":"https://doi.org/10.4172/2155-6180.1000391","url":null,"abstract":"In this study, first of all, a definition of sets will be explained. In addition to the definition of the set known in mathematics, new approaches will be presented. Ten rules about the set definition model will be proposed. 1. It is necessary to determine the title and descriptive identity of the set. 2. It is necessary to determine the address of the set. 3. Specifying the appropriate boundary of the set of creature. 4. Specifying the time of the cluster. 5. The status of the cluster action must be specified. 6. The type and group of the cluster should be specified. 7. The status of live or non-live clusters should be indicated. 8. The load of the cluster element must be specified. 9. If possible, the gender of the cluster element must be specified. 10. The scientific name of the cluster elements must be specified. Out of these ten rules: the cluster must be specified if there is a special case. Later, the definitions of these rules will be presented with examples. Also gender, load, location, action, group, live and inanimate etc., cluster properties will be defined. Examples of animate and inanimate creature sets will be presented. After all, we gain mathematical cluster consciousness of all animate and inanimate creatures and systems in the nature. In addition to this; Natural, artificial, virtual, objective, mental, light etc., examples of sets will be given.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"9 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.4172/2155-6180.1000391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43994052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Estimating and Testing the Effect of Delayed Marriage on Fertility 延迟婚姻对生育能力影响的评估和检验

Journal of biometrics & biostatistics Pub Date : 2018-01-30 DOI: 10.4172/2155-6180.1000387

Uzuke Ca, O. Ica

引用次数: 0

Deep Learning Methods for Predicting Disease Status Using Genomic Data. 利用基因组数据预测疾病状态的深度学习方法。

Journal of biometrics & biostatistics Pub Date : 2018-01-01 Epub Date: 2018-12-11

Qianfan Wu, Adel Boueiz, Alican Bozkurt, Arya Masoomi, Allan Wang, Dawn L DeMeo, Scott T Weiss, Weiliang Qiu

{"title":"Deep Learning Methods for Predicting Disease Status Using Genomic Data.","authors":"Qianfan Wu, Adel Boueiz, Alican Bozkurt, Arya Masoomi, Allan Wang, Dawn L DeMeo, Scott T Weiss, Weiliang Qiu","doi":"","DOIUrl":"","url":null,"abstract":"<p><p>Predicting disease status for a complex human disease using genomic data is an important, yet challenging, step in personalized medicine. Among many challenges, the so-called curse of dimensionality problem results in unsatisfied performances of many state-of-art machine learning algorithms. A major recent advance in machine learning is the rapid development of deep learning algorithms that can efficiently extract meaningful features from high-dimensional and complex datasets through a stacked and hierarchical learning process. Deep learning has shown breakthrough performance in several areas including image recognition, natural language processing, and speech recognition. However, the performance of deep learning in predicting disease status using genomic datasets is still not well studied. In this article, we performed a review on the four relevant articles that we found through our thorough literature search. All four articles first used auto-encoders to project high-dimensional genomic data to a low dimensional space and then applied the state-of-the-art machine learning algorithms to predict disease status based on the low-dimensional representations. These deep learning approaches outperformed existing prediction methods, such as prediction based on transcript-wise screening and prediction based on principal component analysis. The limitations of the current deep learning approach and possible improvements were also discussed.</p>","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"9 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530791/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"37274873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tipping Points: A Statistical Comparison between Humans and Conodonts 临界点:人类和牙形刺之间的统计比较

Journal of biometrics & biostatistics Pub Date : 2018-01-01 DOI: 10.4172/2155-6180.1000396

C. Qualls, S. Lucas, Ali Am, O. Appenzeller

引用次数: 1