Search Results - "Pfitzner, Bjarne"

Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-ray Data by Ziegler, Joceline, Pfitzner, Bjarne, Schulz, Heinrich, Saalbach, Axel, Arnrich, Bert

“…Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical…”
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Federated Learning for Activity Recognition: A System Level Perspective by Kalabakov, Stefan, Jovanovski, Borche, Denkovski, Daniel, Rakovic, Valentin, Pfitzner, Bjarne, Konak, Orhan, Arnrich, Bert, Gjoreski, Hristijan

“…The past decade has seen substantial growth in the prevalence and capabilities of wearable devices. For instance, recent human activity recognition (HAR)…”
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Computational approaches to alleviate alarm fatigue in intensive care medicine: A systematic literature review by Chromik, Jonas, Klopfenstein, Sophie Anne Ines, Pfitzner, Bjarne, Sinno, Zeena-Carola, Arnrich, Bert, Balzer, Felix, Poncette, Akira-Sebastian

“…Patient monitoring technology has been used to guide therapy and alert staff when a vital sign leaves a predefined range in the intensive care unit (ICU) for…”
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Human Activity Recognition with Wearables using Federated Learning by Borche Jovanovski, Stefan Kalabakov, Daniel Denkovski, Valentin Rakovic, Bjarne Pfitzner, Orhan Konak, Bert Arnrich, Hristijan Gjoreski

“…The increasing use of Wearable devices opens up the use of a wide range of applications. Using different models, these devices can be of great use in Human…”
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Federated Learning for Network Intrusion Detection in Ambient Assisted Living Environments by Cholakoska, Ana, Gjoreski, Hristijan, Rakovic, Valentin, Denkovski, Daniel, Kalendar, Marija, Pfitzner, Bjarne, Arnrich, Bert

“…Given the Internet of Things’ rapid expansion and widespread adoption, it is of great concern to establish secure interaction between devices without worsening…”
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Enhancing Preoperative Outcome Prediction: A Comparative Retrospective Case-Control Study on Machine Learning versus the International Esodata Study Group Risk Model for Predicting 90-Day Mortality in Oncologic Esophagectomy by Winter, Axel, van de Water, Robin P, Pfitzner, Bjarne, Ibach, Marius, Riepe, Christoph, Ahlborn, Robert, Faraj, Lara, Krenzien, Felix, Dobrindt, Eva M, Raakow, Jonas, Sauer, Igor M, Arnrich, Bert, Beyer, Katharina, Denecke, Christian, Pratschke, Johann, Maurer, Max M

“…Risk prediction prior to oncologic esophagectomy is crucial for assisting surgeons and patients in their joint informed decision making. Recently, a new risk…”
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DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder by Pfitzner, Bjarne, Arnrich, Bert

“…Federated learning (FL) is getting increased attention for processing sensitive, distributed datasets common to domains such as healthcare. Instead of directly…”
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Sensor-Based Obsessive-Compulsive Disorder Detection With Personalised Federated Learning by Kirsten, Kristina, Pfitzner, Bjarne, Loper, Lando, Arnrich, Bert

“…The mental illness Obsessive-Compulsive Disorder (OCD) is characterised by obsessive thoughts and compulsive actions. The latter can occur as repetitive…”
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Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data by Ziegler, Joceline, Pfitzner, Bjarne, Schulz, Heinrich, Saalbach, Axel, Arnrich, Bert

“…Privacy regulations and the physical distribution of heterogeneous data are often primary concerns for the development of deep learning models in a medical…”
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Data Augmentation of Kinematic Time-Series From Rehabilitation Exercises Using GANs by Albert, Justin, Glockner, Pawel, Pfitzner, Bjarne, Arnrich, Bert

“…Machine learning, especially deep learning, offers great potential for medical applications. However, deep learning algorithms need a vast amount of training…”
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Tangle Ledger for Decentralized Learning by Schmid, Robert, Pfitzner, Bjarne, Beilharz, Jossekin, Arnrich, Bert, Polze, Andreas

“…Federated learning has the potential to make machine learning applicable to highly privacy-sensitive domains and distributed datasets. In some scenarios,…”
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Differentially-Private Federated Learning with Non-IID Data for Surgical Risk Prediction by Pfitzner, Bjarne, Maurer, Max M., Winter, Axel, Riepe, Christoph, Sauer, Igor M., Van de Water, Robin, Arnrich, Bert

“…Federated learning (FL) has emerged as a promising solution to deal with the privacy concerns which often limit access to data for training machine learning…”
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Implicit Model Specialization through DAG-based Decentralized Federated Learning by Beilharz, Jossekin, Pfitzner, Bjarne, Schmid, Robert, Geppert, Paul, Arnrich, Bert, Polze, Andreas

“…Federated learning allows a group of distributed clients to train a common machine learning model on private data. The exchange of model updates is managed…”
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Perioperative Risk Assessment in Pancreatic Surgery Using Machine Learning by Pfitzner, Bjarne, Chromik, Jonas, Brabender, Rachel, Fischer, Eric, Kromer, Alexander, Winter, Axel, Moosburner, Simon, Sauer, Igor M., Malinka, Thomas, Pratschke, Johann, Arnrich, Bert, Maurer, Max M.

“…Pancreatic surgery is associated with a high risk for postoperative complications and death of patients. Complications occur in a variable interval after the…”
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Poisoning Attacks with Generative Adversarial Nets by Muñoz-González, Luis, Pfitzner, Bjarne, Russo, Matteo, Carnerero-Cano, Javier, Lupu, Emil C

“…Machine learning algorithms are vulnerable to poisoning attacks: An adversary can inject malicious points in the training dataset to influence the learning…”
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