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- Toet, Willem (author), van der Plas, Luuk (author), van Wijngaarden, Dirk (author), Aberson Bodewes, Niek (author), van Lith, Jochem (author) student report 2023
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Josemans, Sabine (author)Introduction<br/>In the Netherlands, approximately five thousand people are dependent on maintenance hemodialysis (HD) treatment. The one-year mortality of this patient population in 2021 was as high as 18%. A significant contributor to this high mortality and burden on HD patients is the high incidence of intradialytic hypotension (IDH), which...master thesis 2023
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Ries, Maxmillan (author)Training deep learning models for time-series prediction of a target population often requires a substantial amount of training data, which may not be readily available. This work addresses the challenge of leveraging multiple related sources of time series data in the same feature space to improve the prediction performance of a deep learning...master thesis 2023
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van der Voort, Niels (author)Heart rate data and other data collected by consumer-grade wearable devices can give away quite useful information about the user. It can for example be used by machine learning algorithms such as Deep Neural Networks (DNN) to learn patterns about cardiovascular disease and fitness, or be used for identification. Heart rate patterns can also...bachelor thesis 2023
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Chiriţă, Matei (author)The aim of this paper is to complete the gap in the knowledge and experiment using as little as only the heart rate of some subjects to manage to successfully authorise them in some supposed system. The focus will be on the Gaussian Mixture model and the One Class Support Vector Machine, both outlier detectors, because most of the past research...bachelor thesis 2023
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Harthoorn, Jip (author)Advancements in the precision and accuracy of consumer-grade wearables, such as a Fitbit, have enabled the identification and therefore authentication of individuals based on their emitted heart frequencies using these wrist-worn devices. With this type of authentication, a password is essentially sent out every second. This makes it a perfect...bachelor thesis 2023
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Wubben, Luuk (author)Outlier detection is an essential part of modern systems. It is used to detect anomalies in behaviour or performance of systems or subjects, such as fall detection in smartwatches or voltage irregularity detection in batteries. This provides early indications of something of potential problems.<br/><br/>A part of outlier detection that is not...bachelor thesis 2023
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Grzejdziak, Michał (author)Neural networks are commonly initialized to keep the theoretical variance of the hidden pre-activations constant, in order to avoid the vanishing and exploding gradient problem. Though this condition is necessary to train very deep networks, numerous analyses showed that it is not sufficient. We explain this fact by analyzing the behavior of the...master thesis 2023
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- ter Horst, Ynze (author) master thesis 2023
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Ihaddouchen, Imane (author)Introduction: In intensive care units (ICU), the most significant life support technology for patients with acute respiratory failure is mechanical ventilation. A mismatch between ventilatory support and patient demand is referred to as patient-ventilator asynchrony (PVA), and it is associated with a series of adverse...master thesis 2023
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Meester, Anne (author)Introduction: Critically ill children admitted to the Paediatric Intensive Care Unit (PICU) have a high risk of disruption of their normal sleep rhythm, which is associated with disturbances in physiology and negative effects on psychological and cognitive functioning. There is a need for real-time, automatic sleep monitoring to minimise...master thesis 2023
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van der Wal, Robin (author)Multiple Instance Learning (MIL) is a type of semi-supervised machine learning used recently in medical and multi-media fields. In MIL, instead of a single feature vector, a set of feature vectors has to be classified. Standard MIL algorithms assume that only some of these vectors are useful for building a classifier. This paper extends the...master thesis 2022
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Freyer, Caroline (author)Outlier detection in time series has important applications in a wide variety of fields, such as patient health, weather forecasting, and cyber security. Unfortunately, outlier detection in time series data poses many challenges, making it difficult to establish an accurate and efficient detection method. In this thesis, we propose the Random...master thesis 2022
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van 't Wout, Maarten (author)Handling missing values is crucial for accurately forecasting time series with different sampling rates. In stock price prediction, for example, the daily stock prices and quarterly valuation figures are sampled at a different rate, and both are useful in estimating the daily stock price’s future. This research proposes combining imputation...master thesis 2021
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Lange, Berend-Jan (author)Artificial neural networks are the key driver of progress in various semantic computer vision tasks such as age prediction and digit classification. For the successful application of neural network algorithms, the representation of the data is an important factor. A good representation can significantly simplify a regression or prediction task....master thesis 2021
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Hiemstra, Floor (author)Introduction: Sleep deprivation is commonly encountered in critically ill children admitted to the pediatric intensive care unit (PICU) and is associated with poor clinical outcome. Automated electroencephalography (EEG)-based depth of sleep monitoring enables real-time continuous study of sleep in PICU patients without the...master thesis 2021
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Biesheuvel, Julian (author)Yes, convolutional neural networks are domain-invariant, albeit to some limited extent. We explored the performance impact of domain shift for convolutional neural networks. We did this by designing new synthetic tasks, for which the network’s task was to map images to their mean, median, standard deviation, and variance pixel intensities. We...bachelor thesis 2021
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Lamon, Julien (author)With an expectation of 8.3 trillion photos stored in 2021 [1], convolutional neural networks (CNN) are beginning to be preeminent in the field of image recognition. However, with this deep neural network (DNN) still being seen as a black box, it is hard to fully employ its capabilities. A need to tune hyperparameters is required to have a robust...bachelor thesis 2021
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Thakoersingh, Ratish (author)This research provides an overview on how training Convolutional Neural Networks (CNNs) on imbalanced datasets affect the performance of the CNNs. Datasets could be imbalanced as a result of several reasons. There are for example naturally less samples of rare diseases. Since the network is trained less on those instances, this might lead to...bachelor thesis 2021
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den Heijer, Remco (author)Does a convolutional neural network (CNN) always have to be deep to learn a task? This is an important question as deeper networks are generally harder to train. We trained shallow and deep CNNs and evaluated their performance on simple regression tasks, such as computing the mean pixel value of an image. For these simple tasks we show that...bachelor thesis 2021