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 20 of 290 for “"cancer diagnosis"”.
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A Predictive Model for Pancreatic Cancer Diagnosis
… (PDAC), a specific type of pancreatic cancer, has a five-year survival rate of 8.5% and is the third-deadliest cancer in the United States. However, earlier detection can raise survival rates dramatically. In this thesis, we investigate the hypothesis that predictive models from a …
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Aspects of skin cancer diagnosis in clinical practice
Skin cancer incidence is increasing in fair-skinned populations. The three most common skin cancers are basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and malignant melanoma (MM). A correct diagnosis is crucial for an efficient and tailored treatment for the skin cancer patient. The …
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Imaging Based Models to Improve Lung Cancer Diagnosis
Per the American Cancer Society, lung cancer is the second most common cancer in both men and women, and the leading cause of cancer death, making up almost 25% of all cancer deaths. As such, it is pivotal to better detect and locate lung cancer from chest radiographs (x-rays) and computed …
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Optical reflectance spectroscopy for cancer diagnosis : analysis and modeling
… is motivated by the detection of oral cancer, but some of the methods developed can be generalized to epithelial cancers of other sites. Two main topics are covered in this dissertation: Analysis and Modeling. For analysis, the focus is on developing algorithms to make diagnostic …
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Novel Optical Endoscopes for Early Cancer Diagnosis and Therapy
Imaging is the only medical tool currently capable of non-invasively capturing detailed, real time and spatially resolved biochemical information in vivo and thus delineating disease so that non-invasive curative resection or treatment of the affected area can take place. Though visible and near …
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Cancer Diagnosis During Pregnancy: Evaluating The Challenges Faced By Oncologists
<p>Cancer during pregnancy is occurring more often than in the past, and it is estimated that cancer is diagnosed in approximately 1/1000 pregnancies. A consensus exists that management of these patients should prioritize survival of the mother and minimize teratogenic effects to the fetus, and …
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One-Shot Learning Model for Cancer Diagnosis from Histopathological Images
Cancer diagnosis from tissue biomarker scoring is a vital technique used in determining type and grade of cancer. This is a significant part of workload for pathologists, the process is tedious, time consuming, subjective, error prone and lacks inter-pathologist agreement. Thousands of patients are …
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Radiolabeled Bombesin Analogs to Improve Prostate Cancer Diagnosis by PET Imaging
… G. Ce récepteur est fortement exprimé dans le cancer de la prostate, il est ainsi un biomarqueur potentiel pour ce cancer. La bombésine est un peptide de 14 acides aminés qui se lie avec une forte affinité au GRPR. Les analogues radio-marqués de la bombésine ont été utilisés intensivement pour …
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Magnetically Actuated Microrobots for Tissue Elasticity Mapping in Colorectal Cancer Diagnosis
Colorectal cancer is a major global health issue, ranking among the leading causes of cancer-related mortality. Early detection significantly improves patient outcomes; however, current diagnostic methods such as colonoscopy and traditional imaging primarily rely on visual inspection, limiting …
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Structure-based design of unnatural glycopeptides for cancer diagnosis and therapy
… produce anticuerpos capaces de reconocer células cancerígenas humanas que expresan MUC1 asociado a tumores en su superficie. En modelos murinos de adenocarcinoma de colon y cáncer de páncreas, la vacuna ha demostrado ser eficaz tanto en aplicaciones profilácticas como terapéuticas, retrasando …
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Analyzing Communication in Mother-Daughter Dyads Following the Mother's Cancer Diagnosis
The American Cancer Society estimates nearly 1.5 million Americans will be diagnosed with cancer this year. Existing on cancer and its effects on family communication indicate there are few things that have the potential to shake a family to its core like a serious illness (Anderson & Geist Martin, …
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Statistical aspects of elastic scattering spectroscopy with applications to cancer diagnosis
… is a non-invasive and real-time in vivo optical diagnosis technique sensitive to changes in the physical properties of human tissue, and thus able to detect early cancer and precancerous changes. This thesis focuses on the statistical issue on how to eliminate irrelevant variations in the …
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Model-Based Genomic/Proteomic Signal Processing in Cancer Diagnosis and Prediction
… of gene/protein expressions between normal and cancer subjects. In the literature, various data-driven methods have been proposed, i.e. clustering and machine learning methods. In this thesis, an alternative model-driven approach is proposed. The proposed dependence model focuses on the …
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Development of non-invasive techniques for bladder cancer diagnosis and therapy
Bladder cancer is among the most common cancers in the UK, responsible for significant patient morbidity. Current techniques for detection suffer from low sensitivity, particularly for early stage disease, therefore new techniques are urgently sought.<br/><br/>Among the suggested techniques to …
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Breast cancer diagnosis using Fourier transform infrared imaging and statistical learning
Cancer alters both the morphological and the biochemical properties of multiple cell types in a tissue. Generally, the morphology of epithelial cells is practically used for routine disease diagnoses. Current histopathological diagnosis involves manual interpretation of stained images for patient …
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Towards a Reliable Deep Learning Framework for Prostate Cancer Diagnosis using Ultrasound
Reliable prostate cancer (PCa) detection using ultrasound is crucial for improving patient outcomes. Developing deep learning (DL) models for PCa detection is hindered by noisy labels and cancer heterogeneity. The purpose of this work is to develop a clinically applicable framework for DL-based …
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