Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"Screening trial"”.
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Evaluation of the PLCOM2012 Risk Prediction Model and National Lung Screening Trial Criteria for Selecting Individuals for Lung Cancer Screening
… cause of cancer death in North America. Cancer screening trials, such as the PLCO (Prostate, Lung, Colorectal and Ovarian) and NLST (National Lung screening trial) evaluate LC mortality. There has been a growing interest in risk prediction modelling for selecting high-risk individuals for LC …
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Associations Between Personal Cancer History and Lung Cancer Risk
… from the Prostate, Lung, Colorectal and Ovarian Screening (PLCO) Cancer Screening Trial (N = 154,901) and National Lung Screening Trial (N = 53,452) were analysed. Logistic regression models were used to assess the relationships between each variable of interest and 6-year lung cancer risk. …
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Improving Lung Cancer Risk Prediction: Integration of Novel Predictors and Modelling Using Machine Learning Random Forest versus the Validated PLCOm2012 Logistic Regression Model
… are ineffective, leading to poor prognosis. LC screening using low-dose computed tomography is shown to be effective for early detection of LC to reduce LC mortality. The goal of this study was to develop a superior LC risk prediction model compared to the current established Prostate, Lung, …
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Lung cancer malignancy predication with recurrent neural networks
… diagnose lung cancer. In the past decade, new screening pro- tocols have been enacted that advise high-risk patients to get annual CT screenings to monitor any suspicious lesions found in the lungs. This change increases the availability of CT scans and the number of scans per patient for …
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Associations between Selected Dietary Factors, Selected Obesity-Related Metabolic Markers (Leptin, C-peptide, and High-sensitivity C-reactive Protein), and Lung Cancer: A Matched Case-Control Study Nested in the Prospective PLCO Trial
… Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial were analyzed. Linear regression models were used to describe the associations between quantitative variables. The relationships between variables of interest and lung cancer were studied by logistic regression modelling. …
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Sybil: Predicting Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography
… computed tomography (LDCT) for Jung cancer screening is effective, though most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesize that a deep learning model assessing …
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Targeting the human papillomavirus for prevention of cervical cancer
… efficacy data on HPV testing in primary screening Among 72 cervical cancers in Mozambique, HPV 16 and 18 were the most frequent HPV types (69% of cases). Comparing 108 cervical cancers cases and 517 matched controls nested within a population-based cohort in Taiwan, HPV 16 seropositivity …
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The Association between Serum Cancer Antigen 125 (CA 125) and Risk of Lung Cancer in Females: Assessing the Possibilities for Early Detection
… Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) randomized controlled trial (RCT). The associations between explanatory variables and lung cancer were evaluated using multivariable logistic regression. Each multivariable logistic regression model was adjusted for age, …
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Towards Fully Automated Volumetric Analysis of Lung Nodules in Computed Tomography
… growth in 1,378 patients from the National Lung Screening Trial; we estimate a median nodule volume-doubling time of 791.23 days across all nodules from the patients that do not receive a cancer diagnosis and a median nodule volume-doubling time of 637.38 days across all nodules from the patients …
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Imaging Based Models to Improve Lung Cancer Diagnosis
… risk prediction model to mimic the radiologist screening workflow of using multiple screening images when available. We develop our methods on chest radiograph data from the National Institute of Health (NIH) dataset and low dose computed tomography (LDCT) data from the National Lung Screening …
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Mammographic density in relation to breast cancer Tumor characteristics, mode of detection, and density assessments
… in invasive breast cancer. Furthermore, in screening detected breast cancer, higher mammographic density was associated with lower histological grade, although the evidence for this was weak. Finally, our findings in clinically detected breast cancer, but not in cancers detected during …
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Analysis of the Stakeholder Derived Conceptual Models and Exploration of Lung Cancer Screening Barriers in a Medically Underserved Area
… search to find an accurate and reliable screening test. National Cancer Institute's National Lung Screening Trial (NLST) found that annual screening with Low-Dose CT (LDCT) for asymptomatic patients aged 55 to 74, with a smoking history of at least 30 pack-years, and smokers who quit less …
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Survival analysis for lung cancer patients
… thesis is based on the existing National Lung Screening Trial (NLST) dataset and provides in-depth analysis of different features influencing lung cancer prognosis. We added nodule annotations to the NLST dataset and extracted radiomic features from each nodule. Using the newly acquired …
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Breast cancer screening in an urban, Swedish population Aspects of non-attendance, interval cancers and over-diagnosis
Service screening with mammography was implemented in Sweden in the late 80's, following the results from trials in Sweden and abroad. A high rate of attendance, a high diagnostic accuracy and treatment in accordance with established guidelines are key circumstances for an effective screening …
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Bayesian Adaptive Designs For Early Phase Clinical Trials
… designs for phase I and phase II clinical trials. It includes three specific topics: <strong>(1)</strong> proposing a novel two-dimensional dose-finding algorithm for biological agents, <strong>(2)</strong> developing Bayesian adaptive screening designs to provide more efficient and ethical …