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Objective. The Cochrane risk of bias tool (CRoB) is one of the most widely used tools for assessing the risk of bias of clinical trials. However, it was criticized for its poor inter-rater reliability, lack of clear and detailed guidelines for its application, and no clear distinguishing between reporting quality from real quality in implementation. This study aims to develop a framework (or improved CRoB, iCRoB) so as to improve the inter-rater reliability of the CRoB in its first 4 domains: sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment, through providing: i) a structured pathway for assessing risk of bias assessment; and ii) a comprehensive dictionary of scenarios for each domain. / Methods. The study is consisted of 4 steps: / i) Step 1: Develop a step-by-step structured pathway for assessing the risk of bias. / ii) Step 2: Identify and summarize possible scenarios that are used in literature to describe a domain in clinical trials by using a qualitative content analysis approach. A random sample of 100 Cochrane systematic reviews (SRs) was taken from the Cochrane Database of Systematic Reviews. Each review was carefully scrutinized for this purpose. / iii) Step 3: Merge the scenarios identified from the sample with those already provided in the CRoB. The combined list of scenarios extends the current coverage of the CRoB and forms a more comprehensive dictionary of scenarios for use in the future. The bias assessment pathway and the new dictionary of scenarios in combination are the new components added or contribution to the CRoB to form the iCRoB. / v) Step 4: Conduct a randomized controlled study that allocated at random 8 raters equally into either using the CRoB or our new iCRoB. 150 clinical trials were randomly selected from the fore-mentioned 100 SRs for the inter-rater reliability comparison. Both inter-rater reliability among individual raters (measured with Fleiss’ κ) and that across rater pairs (measured with weighted Cohen’s κ) were computed. Data analyses were conducted by using STATA version 13.0. / Results. A structured pathway for systematically assessing bias was designed, which helps classify a study into one of 5 categories for each risk of bias domain based on the information provided in the report of a trial: Category A: a trial reports in details how a bias reduction method was conducted and it is also deemed by the assessor to be conducted adequately; Category B: a trial reports in details how a bias reduction method was conducted but it is deemed by the assessor to be conducted inadequately; Category C: a trial reports that a bias reduction method was conducted but no detailed description was given which can be used to judge whether it was done adequately; Category D: a trial reports that a bias reduction method was not conducted; Category E: a trial does not mention at all whether or not a bias reduction method was conducted. / A total of 34, 36, 26 and 20 scenarios were generated for sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment, respectively. We extended the current CRoB list of scenarios by a number of 20, 23, 26 and 20 respectively for the 4 bias reduction domains. / Our trial results showed that the iCRoB had a higher inter-rater reliability across rater pairs than the original CRoB for every bias reduction domain. The weighted κ was 0.71 and 0.81 for sequence generation respectively for CRoB and iCRoB; 0.53 and 0.61 for allocation concealment respectively for CRoB and iCRoB; 0.56 for blinding of participants and personnel in CRoB, 0.68 for blinding of participants and 0.70 for blinding of personnel ini CRoB; and 0.19 and 0.43 for blinding of outcome assessment respectively for CRoB and iCRoB. / Conclusion. We developed the iCRoB including a standard pathway and extended substantively the dictionary of scenarios for making the judgement on risk of bias in the reports of clinical trials. Our iCRoB showed a higher reliability than the current CRoB in all the domains examined. The iCRoB can be recommended for improving the assessment of bias in clinical trials. / 目的：考柯藍偏倚風險評估工具(CRoB)是最廣泛應用的用於評價臨床試驗偏倚風險的工具之一。然而，CRoB 有以下三個缺陷：評價者間信度低，缺乏明確和詳細的應用說明和沒有明確區分報告質量和方法學質量。本研究擬制定一個新的工具iCRoB 用以提高CRoB 前4 項指標的評價者間信度。這4項指標分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法。本研究通過以下2 點實現這一目的：i) 提供一個結構化路徑用以評估偏倚風險；ii) 為每個研究指標提供一個廣泛包含偏倚風險評估相關描述場景的字典。 / 方法：本研究包含以下4 個步驟： / 第1 步：制定一個用以評估偏倚風險的結構化路徑。 / 第2 步：從考柯藍系統綜述數據庫中隨機抽取100 篇系統綜述，應用定性內容分析法從中確定並總結出臨床試驗中與偏倚風險相關的可能的描述場景。 / 第3 步：將從100 個樣本中總結的描述場景與CRoB 中已有的場景合併，從而擴大CRoB 的描述場景的覆蓋範圍，得到一個更廣泛包含偏倚風險評估相關描述場景字典。偏倚風險評估的結構化路徑和包含場景描述的字典共同形成了本研究中新制定的iCRoB，用以評估臨床試驗的偏倚風險。 / 第4 步：在一個隨機對照研究中，8 名評價者被隨機平均分配至CRoB 組或者iCRoB 組。在上述100個系統綜述所納入的臨床試驗中隨機抽取150 個臨床試驗用以比較CRoB 和iCRoB 的評價者間信度。評價者間信度的比較包括個體評價者間信度（用Fleiss’κ 測量）和配對評價者間信度(用加權Cohen’s κ 測量)的比較。數據採用Stata 13.0 進行統計分析。 / 結果：本研究成功的制定了一個用於系統評價偏倚風險的結構化路徑，在該結構化路徑中，每個偏倚風險相關的指標在一個臨床研究中將分為以下5 類： / A 類：臨床試驗詳細描述了預防偏倚的措施的實施，根據描述可以判定該措施的實施能預防偏倚的產生; B 類：臨床試驗詳細描述了預防偏倚的措施的實施，根據描述可以判定該措施的實施不能預防偏倚的產生; C 類：臨床試驗報告採取了預防偏倚的措施，但未描述這一過程如何實施，從而無法判斷其實施是否正確; D 類：臨床試驗報告沒有採取任何預防偏倚的措施; E 類：臨床試驗沒有報告是否採取了預防偏倚的措施。 / 本研究分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法收集了34，36，26 和20 個描述場景。與CRoB 提供的描述場景比較，iCRoB 分別為隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法增加了20，23，26 和20 個新的描述場景。 / 隨機對照試驗結果顯示，iCRoB 中每個研究指標的配對評價者間信度均高於CRoB，其中，隨機序列生成加權κ 為0.71（CRoB）和0.81（iCRoB），分配隱藏加權κ 為0.53（CRoB）和0.61（iCRoB），對研究對象和研究者實施盲法加權κ 為0.56（CRoB），對研究對象實施盲法加權κ 為0.68（iCRoB），對研究者實施盲法加權κ 為0.70（iCRoB），對結局評估者實施盲法加權κ 為0.19（CRoB）和0.43（iCRoB）。 / 結論：本研究通過制定一個由偏倚風險評估的結構化路徑和包含場景描述的字典組成的iCRoB，用以改善CRoB 中對臨床試驗中隨機序列生成，分配隱藏，對研究對象和研究者實施盲法，和對結局評估者實施盲法偏倚風險評估過程。相比於CRoB，iCRoB 在每個研究指標中均顯示出更好的配對評價者間信度。這些結果證明評價者間信度可以通過提供結構化偏倚風險評估路徑和更全面的描述場景字典而提高。 / Wu, Xinyin. / Thesis Ph.D. Chinese University of Hong Kong 2014. / Includes bibliographical references (leaves 93-105). / Abstracts also in Chinese. / Title from PDF title page (viewed on 09, September, 2016). / Wu, Xinyin. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.y066 / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only.

The Neonatal Intensive Care Unit (NICU) is a hospital ward specializing in looking after premature and ill newborn babies. Working in such a busy and complex environment is not easy and sophisticated equipment is used to help the daily work of the medical staff . Computers are used to analyse the large amount of monitored data and extract hidden information, e.g. to detect interesting events. Unfortunately, one group of important events lacks features that are recognizable by computers. This group includes the actions taken by the medical sta , for example two actions related to the respiratory system: inserting an endotracheal tube into a baby’s trachea (ET Intubating) or sucking out the tube (ET Suctioning). These events are very important building blocks for other computer applications aimed at helping the sta . In this research, a strategy for detecting these medical actions based on contextual knowledge is proposed. This contextual knowledge specifies what other events normally occur with each target event and how they are temporally related to each other. The idea behind this strategy is that all medical actions are taken for di erent purposes hence may have di erent procedures (contextual knowledge) for performing them. This contextual knowledge is modelled using a point based framework with special attention given to various types of uncertainty. Event detection consists in searching for consistent matching between a model based on the contextual knowledge and the observed event instances - a Temporal Constraint Satisfaction Problem (TCSP). The strategy is evaluated by detecting ET Intubating and ET Suctioning events, using a specially collected NICU monitoring dataset. The results of this evaluation are encouraging and show that the strategy is capable of detecting complex events in an NICU.

Thesis (Ph.D. in Biostatistics) -- University of Colorado Denver, 2008. / Typescript. Includes bibliographical references (leaves 117-119). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;

A endometriose representa uma das doenças mais prevalentes em ginecologia, e afeta cerca de 10 a 15% das mulheres em idade reprodutiva. Apesar do grande aumento da ocorrência desta doença, pouco se sabe sobre sua epidemiologia, principalmente devido à dificuldade metodológica por tratar-se de patologia de definição e etiologia desconhecidas. A prevalência estimada varia de 4% entre mulheres assintomáticas a cerca de 50% entre adolescentes com dismenorréia incapacitante. Fatores de risco pessoais foram descritos, como idade, estado sócio-econômico, estado civil, fatores menstruais, como duração e intervalo dos ciclos e idade da menarca. Sintomas como dismenorréia, dor acíclica, dispareunia de profundidade, alterações urinárias e intestinais cíclicas e infertilidade, também são associados à doença. O objetivo do presente estudo foi determinar uma forma de predizer o diagnóstico cirúrgico baseado no perfil epidemiológico e sintomas da endometriose, através da utilização de um programa interativo para este cálculo. Para tal, analisou-se mulheres com diagnóstico histológico da doença e pacientes sem diagnóstico, pertencentes ao Ambulatório de Ginecologia Preventiva do HC-FMUSP (grupo controle), analisadas através deste programa interativo, constituindo amostra de 1872 pacientes estudadas. A avaliação estatística foi realizada pelos testes do qui-quadrado, t-Student e regressão logística multifatorial. Encontrou-se como fatores de risco significativos a idade, raça, grau de instrução, estado civil, intervalo do ciclo menstrual, presença de dismenorréia, alterações urinárias cíclicas, tipo de infertilidade, além de sintomas mais específicos como disúria, proctorragia e diarréia, dados que foram aplicados através do programa informatizado. Concluiu-se que tal modelo apresenta grande valor para a análise da razão de chances de ocorrência de endometriose na população geral. Análises prospectivas tornam-se imperativas a fim de testarmos tal modelo preditivo para estabelecermos parâmetros que conduziriam ou não à realização de um procedimento invasivo para o diagnóstico da doença. / Advances in understanding the epidemiology of endometriosis have lagged behind other diseases. To determine whether the surgical diagnosis of endometriosis can be predicted using noninvasive tools as epidemiological profile, medical history and symptoms related to the disease, were analyzed women with histological diagnosis of endometriosis and patients without diagnosis, analyzed through an interactive program, constituting a sample of 1872 studied patients. We could conclude that such model presents big value for the analysis of odds ratio to endometriosis in general population. Prospective analysis become imperative in order to create a predictive model to establish parameters that could suggest a surgical procedure.

Shi, Lin. / Thesis (Ph.D.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 171-185). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts in English and Chinese.

Wang, Zexi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2007. / Includes bibliographical references (leaves 63-64). / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 0 --- Introduction --- p.1 / Chapter 1 --- The Design of the Experiments --- p.4 / Chapter 1.1 --- Flies and the Devices --- p.5 / Chapter 1.2 --- Parameter Settings and Interested Information --- p.8 / Chapter 2 --- Video Processing --- p.11 / Chapter 2.1 --- "Videos, Computer Vision and Image Processing" --- p.11 / Chapter 2.2 --- Details in Video Processing --- p.14 / Chapter 3 --- Data Analysis --- p.20 / Chapter 3.1 --- Background --- p.20 / Chapter 3.2 --- Outline of Data Analysis in Our Project --- p.22 / Chapter 4 --- Effect of the Medicine --- p.25 / Chapter 4.1 --- Hypothesis Testing --- p.26 / Chapter 4.2 --- Two-sample t Test --- p.28 / Chapter 5 --- Significance of the Two Factors --- p.32 / Chapter 5.1 --- Background of ANOVA --- p.33 / Chapter 5.2 --- The Model of ANOVA --- p.35 / Chapter 5.3 --- Two-way ANOVA in Our Data Analysis --- p.42 / Chapter 6 --- Regression Model --- p.45 / Chapter 6.1 --- Background of Regression Analysis --- p.47 / Chapter 6.2 --- Polynomial Regression Models --- p.52 / Chapter 6.2.1 --- Background --- p.52 / Chapter 6.2.2 --- R2 and adjusted R2 --- p.53 / Chapter 6.3 --- Model Verification --- p.58 / Chapter 6.4 --- A Simpler Model As the Other Choice --- p.59 / Chapter 6.5 --- Conclusions --- p.60 / Chapter 7 --- Further Studies --- p.61 / Bibliography --- p.62

Thesis (Ph.D. in Biostatistics) -- University of Colorado at Denver and Health Sciences Center, 2006. / Typescript. Includes bibliographical references (leaves 72-75). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;

Thesis (Ph. D.)--University of Alabama at Birmingham, 2008. / Title from first page of PDF file (viewed Sept. 23, 2008). Includes bibliographical references.

Thesis (Ph.D. in Analytic Health Sciences, Dept. of Preventive Medicine and Biometrics) -- University of Colorado Denver, 2007. / Typescript. Includes bibliographical references (leaves 57-59). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;