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Finding Biomarkers for Schizophrenia: Can Machine Learning algorithms identify schizophrenia-related biomarkers within metagenomic data derived from the human gut microbiome?

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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Login with Face and Speaker Recognition

Van Oorschot, J. (author), Catshoek, T. (author), Brand, S. (author)

bachelor thesis 2016

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Optimising a Recommendation Model for Career Discovery

Beker, B. (author), Brugsma, R. (author), Offerijns, J.F. (author)

Recommendation systems are algorithms that aim to predict what items are preferred by a user, based on a recorded history of user activity. Magnet.me is a company which recommends companies and opportunities to students. Potential algorithms for recommendation systems are memory-based and model-based coll aborative filtering, graph- based...

bachelor thesis 2017

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A plug-in infrastructure for the CodeFeedr project

Kuijpers, Jos (author), Quist, Joris (author), Zorgdrager, Wouter (author)

CodeFeedr is a research project at the software engineering division of the Delft University of Technology in collaboration with the Software Improvement Group. The research focuses on a software infrastructure which serves software practitioners in utilizing data-driven decision making. Currently, frameworks like Apache Flink are capable of...

bachelor thesis 2018

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Time series predictions for bank account balances

Kreynen, B.L.L. (author), Olieman, C. (author), van Doorn, F.A. (author), Spanoghe, M. (author)

For our bachelor project we have been using machine learning to predict account balances for a large Dutch bank holding company. The company’s main interest is the integration of machine learning techniques in their systems. To enable this we have been asked to develop a product to predict account balances for the clients of associated banks....

bachelor thesis 2016

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Identifying biological markers in the gut microbiome associated with celiac disease using machine learning

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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Using pre-trained convolutional neural networks to predict maturity levels of strawberries

Buitenweg, Jurriaan (author)

To reduce food waste, the strawberry harvesting process should be optimized. In the modern era, computer vision can provide huge amounts of help. This paper focuses on optimizing pre-trained convolutional neural networks (CNN) to determine the maturity level of strawberries on a 1-10 scale. Here, 1 means unripe and 10 means overripe. Maturity...

bachelor thesis 2022

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Visualisation of Component Alert Data for an Analysis by Machine Learning Algorithms

Boot, J. (author), Hommes, J. (author), Rijsdijk, J. (author)

In recent days, the products and services provided by banks have moved to the digital domain more and more. Since most people rely on these services in their day to day lives, availability and reliability are very important in the success of a bank. In an effort to increase automation in this regard, ING Bank wants to employ machine learning to...

bachelor thesis 2016

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Hadoop in the browser: Simulating MapReduce in the browser

Bilen, H. (author), Zwart, M.D. (author)

With the current increase of user generated data, the need for tools to process large quantities of data is increasing. One of the courses of the Computer Science BSc curriculum is the Big Data Processing course. The Big Data Processing course teaches students ways of doing so. A popular and teached method is using MapReduce, a programming model...

bachelor thesis 2016

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Finding Biomarkers for Type 2 Diabetes

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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Finding biological markers for the prediction of colorectal cancer: Using machine learning methods to identify functional biomarkers in the human gut microbiome

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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The Effect of Color Spaces and Spectra on a Strawberry Prediction Model

Rosenberg, Jaron (author)

The purpose of this research is to reduce food waste by monitoring the ripening process of strawberries in order to optimize the harvesting time. To improve the moment of harvest, we need to know the ripeness of a strawberry. Using data from different color ranges and spaces we should be able to predict the ripeness of a strawberry on a 1-10...

bachelor thesis 2022

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Measuring the size of strawberries using binocular photos

van Melis, Kris (author)

To reduce food waste, it is important to know what strawberries to prioritise for harvesting. Size is an important quality attribute for strawberry. In order to know the size, the depth of the strawberry in the image must been known. To estimate the depth, stereovision gets utilized using binocular images. Since classic stereovision methods are...

bachelor thesis 2022

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Finding biological markers for Parkinson's disease: Using machine learning to analyse metagenomic data

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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Detecting strawberries using different Convolutional Neural Networks

Bechtold, Jeroen (author)

This paper tries to combat the food waste of strawberries during the harvesting steps.<br/>An automatic pipeline must be established to combat this food waste.<br/>One of the steps needed in this pipeline is detecting strawberries in images.<br/>Therefore, this paper aims to find out which Convolutional Neural Network (CNN) can be best used to...

bachelor thesis 2022

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Synthetic data generation for the optimization of strains in metabolic engineering using latent space representations derived from a Conditional Variational Autoencoder

Alwani, Neil (author)

This study investigates the application of generative models for synthetic data generation in pathway optimization experiments within the field of metabolic engineering. Conditional Variational Autoencoders (CVAEs) use neural networks and latent variable distributions to generate new, plausible data samples. We adapt this model by conditioning...

bachelor thesis 2024

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Synthetic data generation for the optimization of strains in metabolic engineering using generative adversarial networks

Jarosz, Marcin (author)

This research investigates the application of Generative Adversarial Networks (GANs) and probabilistic Principal Component Analysis (PPCA) in generating synthetic data for pathway optimization in metabolic engineering. The study aims to compare the performance of these generative models, addressing key questions regarding their utilization, the...

bachelor thesis 2024

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Optimizing strains in Metabolic Engineering: comparative analysis of β-Conditional Variational Auto-encoder and Probabilistic PCA for synthetic data generation

Kirbeyi, Doruk (author)

This research explores the landscape of dataset generation through the lens of Probabilistic Principal Component Analysis (PPCA) and β-Conditional Variational Auto-encoder (β-CVAE) models. We conduct a comparative analysis of their respective capabilities in reproducing datasets that mirror the distribution of the original data that comes from a...

bachelor thesis 2024

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Evaluation of natural language processing embeddings in protein function prediction for bacteria

Cosma, Bianca (author)

<b>Motivation: </b>The development of automated protein function prediction models is essential in closing the gap between the large amount of protein sequence data available and the fraction of validly annotated data. Recent approaches to function prediction rely on unsupervised deep learning models, through which protein sequences are...

bachelor thesis 2022

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Explainable artificial intelligence in forensics: realistic explanations for number of contributor predictions of DNA profiles

Veldhuis, Marthe (author)

Using machine learning to determine the number of contributors (NOC) in short tandem repeat (STR) mixture DNA profiles has been shown to obtain good accuracy. However, the models used so far are not transparent to users as they only output a prediction without any reasoning for that conclusion. Therefore, we leverage techniques from the field of...

master thesis 2021