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de Bie, Melissa (author)Introduction<br/>Patient-ventilator asynchrony (PVA) poses a significant challenge in the management of mechanically ventilated patients, contributing to adverse clinical outcomes. Current methods of detecting PVA rely on visual assessment by clinicians, leading to subjectivity and inconsistency. Therefore, there is a need for automated...master thesis 2024
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van Winden, Brian (author)Introduction<br/>Approximately 9 in 1000 children are born with congenital heart disease (CHD), of whom a quarter are classified as critical CHD (CCHD) and require an intervention within their first year. Monitoring these patients in the Paediatric Intensive Care Unit (PICU) is crucial, yet with increasing amounts of data, detecting subtle...master thesis 2024
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Bakker, Bo (author)Data-driven approaches are a promising new addition to the list of available strategies for solving Partial Differential Equations (PDEs). One such approach, the Principal Component Analysis-based Neural Network PDE solver, can be used to learn a mapping between two function spaces, corresponding to a PDE. However, the practical limitations of...bachelor thesis 2024
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Kiste, Amund (author)Solving Partial Differential Equations (PDEs) in engineering such as Navier-Stokes is incredibly computationally expensive and complex. Without analytical solutions, numerical solutions can take ages to simulate at great expense. In order to reduce this cost, neural networks may be used to compute approximations of the solution for use during...bachelor thesis 2024
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Lacombe, Pablo (author)This paper presents a comprehensive exploration of a novel method combining Principal Component Analysis (PCA) and Neural Networks (NN) to efficiently solve Partial Differential Equations (PDEs), a fundamental challenge in modeling a wide range of real-world phenomena. Our research extends the work of Bhattacharya et al. by focusing on PCA for...bachelor thesis 2024
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Oerlemans, Carlijn (author)Study objectives: Conventional sleep scoring is based on the scoring criteria of the American Association of Sleep Medicine (AASM) but may not be suited to describe sleep in critically ill children admitted to the Pediatric Intensive Care Unit (PICU). In this study, an anomaly detection model using Gaussian Models trained on sleep stages in data...master thesis 2024
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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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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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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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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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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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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