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Tofacchi, Tommaso (author)
<b>Motivation</b>. DNA molecules mutate thousands of times every day. Some mutations are harmful to human cells, and may lead to the loss of function in important genes involved in DNA damage repair (DDR) mechanisms. Diseases such as tumors can exploit mutations in important, driver DDR genes to rapidly proliferate. Specific patterns of...
master thesis 2024
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de Vries, Chiel (author)
Alzheimer's disease (AD) is becoming more prevalent as the world population gets older. The formation of Amyloid-beta (\AB) plaques is one of the pathologies related to AD. Recent work has shown that the \ab load in brain tissue has a negative correlation with cognitive performance in cognitively healthy centenarians. <br/>This work aims to...
master thesis 2023
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Persianov, Petr (author)
Celiac disease is a genetic autoimmune disorder caused by a negative reaction to gluten associated with alterations in the gut microbiome. This study explored the potential of machine learning models and feature selection methods in identifying biomarkers for celiac disease using gut microbiome data. The performance of several machine learning...
bachelor thesis 2023
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Das, Aratrika (author)
Type 2 Diabetes is a very prevalent disease in current times and leads to significant adverse effects. Recently, there has been a growing interest in the association of the human gut microbiome with respect to chronic diseases like Type 2 Diabetes with the aim to identify biomarkers. In this study, we researched the effect of different machine...
bachelor thesis 2023
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Sloof, Jos (author)
Colorectal cancer (CRC), one of the leading causes of mortality, is challenging to diagnose. By using metagenomic analysis with machine learning methods, this can be done in a non-invasive manner. In this research, a neural network has been trained on relative pathway abundance data, a way to measure the functional potential of a microbiome, in...
bachelor thesis 2023
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Koning, Marilotte (author)
Parkinson's disease (PD) is a neurodegenerative disorder characterized by motor function loss and potential mental and behavioral changes. The identification of biomarkers in the gut microbiota of PD patients can significantly aid in fast and accurate diagnosis. This study investigates the application of machine learning (ML) models, including...
bachelor thesis 2023
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Bastow, Timothy (author)
There is mounting evidence indicating a relation- ship between the gut microbiome composition and the development of mental diseases but the mech- anisms remain unclear. Shotgun sequenced data from 90 schizophrenic patients and 81 sex, age, weight, and location matched controls was used for three machine learning models: Logistic Re- gression,...
bachelor thesis 2023
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te Nijenhuis, Frank (author)
The efficacy of endovascular therapy in large vessel occlusion (LVO) of the anterior circulation is dependent to a high degree on the selection of patients who are likely to benefit from this procedure. To this end, functional outcome prediction based on clinical parameters is an active area of research. In the preoperative screening of LVO...
master thesis 2022
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Peterse, Sjors (author)
In modern neurosurgical practice, a surgeon can see a patient’s fiber tracts (nerve tracts) on a monitor in the operating room. This design study investigates the benefit of adding the uncertainty of the tracts and aims to improve the surgeon’s orientation while reducing visual clutter.<br/><br/>Based on an interview with a neurosurgeon and our...
master thesis 2022
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Drummer, Francesca (author)
Single-cell sequencing allows measuring individual cells' molecular features and their responses to perturbations. Understanding which cells respond to a particular perturbation and how these responses vary across populations can be used to, for example, improve vaccine immunogenicity. However, an exhaustive exploration of single-cell...
master thesis 2022
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Tahur, Nishad (author)
Color information has been shown to provide useful information during image classification. Yet current popular deep convolutional neural networks use 2-dimensional convolutional layers. The first 2-dimensional convolutional layer in the network combines the color channels of the input images, which produces feature maps per channel with only...
master thesis 2022
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Hofland, Jeroen (author)
Generalizing models for new unknown datasets is a common problem in machine learning. Algorithms that perform well for test instances with the same distribution as their training dataset often perform severely on new datasets with a different distribution. This problem is caused by distributional shifts between the training of the model and...
bachelor thesis 2022
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Guan, Zenan (author)
Out-of-Domain (OOD) generalization is a challenging problem in machine learning about learning a model from one or more domains and making the model perform well on an unseen domain. Empirical Risk Minimization (ERM), the standard machine learning method, suffers from learning spurious correlation in the training domain, therefore may perform...
bachelor thesis 2022
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Liu, Anxian (author)
Out-of-domain (OOD) generalization refers to learning a model from one or more different but related domain(s) that can be used in an unknown test domain. It is challenging for existing machine learning models. Several methods have been proposed to solve this problem, and multi-domain calibration is one of these methods. Model selection with the...
bachelor thesis 2022
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Dimitrov, Stoyan (author)
To ensure that a software system operates in the correct way, it is crucial to test it extensively. Manual software testing is severely time-consuming, and developers often underestimate its importance. Consequently, many tools for automatic test generation have been developed during the past decade. EvoSuite is a state-of-the-art tool for...
bachelor thesis 2022
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Kling, Toon (author)
Recently, automating test suite generation is a problem that has drown attention in both industry and academia. One of the tools used to automatically generate test suites is EvoSuite, which is a state-of-the-art tool often used in research. It uses a genetic algorithm, which seeks to maximize certain coverage criteria, such as Branch Coverage...
bachelor thesis 2022
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Toader, Daniela (author)
The perpetual desire for more qualitative software has been an excellent incentive for software engineers to create automated tools to ease and improve the process of software testing. EvoSuite is an example of a state-of-the-art tool that synthesises test cases automatically. It uses a genetic algorithm to produce test cases based on given...
bachelor thesis 2022
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Stranski, Ivan (author)
Software testing is essential for a successful development process, however, it can be troublesome as manually writing tests can be time demanding and error-prone. EvoSuite is a test case generating tool developed to address this [18]. It can generate test cases for different test criteria - Line Coverage, Branch Coverage, Input Diversity, etc....
bachelor thesis 2022
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Kaur, Sukhleen (author)
Survival analysis is a statistical method used to predict when an event will occur. Machine learning survival models have been used in many cancer studies. However, machine learning models may not always be interpretable. The current lack of research for explainable survival analysis for urothelial cancer prompted this study. This study offers...
master thesis 2021
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Nederveen, Tim (author)
Software engineers often lack the domain knowledge needed to validate context specific parts of software. Domain experts do have this knowledge needed to validate the software, but often lack the expertise and tools to apply this knowledge in a way that tests the software product. Based on a case study at business-software company Exact, this...
master thesis 2021
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