Zobrazeno 1 - 10
of 887
pro vyhledávání: '"DEKKER, Andre"'
We reply to the comments on our proposed privacy preserving n-party scalar product protocol made by Liu. In their comment Liu raised concerns regarding the security and scalability of the $n$-party scalar product protocol. In this reply, we show that
Externí odkaz:
http://arxiv.org/abs/2409.10057
Autor:
Mateus, Pedro, Garst, Swier, Yu, Jing, Cats, Davy, Harms, Alexander G. J., Birhanu, Mahlet, Beekman, Marian, Slagboom, P. Eline, Reinders, Marcel, van der Grond, Jeroen, Dekker, Andre, Jansen, Jacobus F. A., Beran, Magdalena, Schram, Miranda T., Visser, Pieter Jelle, Moonen, Justine, Ghanbari, Mohsen, Roshchupkin, Gennady, Vojinovic, Dina, Bermejo, Inigo, Mei, Hailiang, Bron, Esther E.
Biological age scores are an emerging tool to characterize aging by estimating chronological age based on physiological biomarkers. Various scores have shown associations with aging-related outcomes. This study assessed the relation between an age sc
Externí odkaz:
http://arxiv.org/abs/2409.01235
Autor:
Zegers, Catharina M L, Witteveen, Annemieke, Schulte, Mieke H J, Henrich, Julia F, Vermeij, Anouk, Klever, Brigit, Dekker, Andre
Publikováno v:
JMIR Formative Research, Vol 5, Iss 3, p e17456 (2021)
The health care sector can benefit considerably from developments in digital technology. Consequently, eHealth applications are rapidly increasing in number and sophistication. For successful development and implementation of eHealth, it is paramount
Externí odkaz:
https://doaj.org/article/a4ded2e478ed4ddbb425bc122bde610c
Federated learning allows us to run machine learning algorithms on decentralized data when data sharing is not permitted due to privacy concerns. Ensemble-based learning works by training multiple (weak) classifiers whose output is aggregated. Federa
Externí odkaz:
http://arxiv.org/abs/2402.12142
Federated learning makes it possible to train a machine learning model on decentralized data. Bayesian networks are probabilistic graphical models that have been widely used in artificial intelligence applications. Their popularity stems from the fac
Externí odkaz:
http://arxiv.org/abs/2210.17228
Autor:
Osong, Biche, Hasannejadasl, Hajar, van der Poel, Henk, Vanneste, Ben, van Roermund, Joep, Aben, Katja, Van Soest, Johan, Van Oort, Inge, Hochstenbach, Laura, Bloemen- van Gurp, Esther J., Dekker, Andre, Fijten, Rianne R.R.
Publikováno v:
In Technical Innovations & Patient Support in Radiation Oncology September 2024 31
Given the impact of health literacy (HL) on patients outcomes, limited health literacy (LHL) is a major barrier in cancer care globally. HL refers to the degree in which an individual is able to acquire, process and comprehend information in a way to
Externí odkaz:
http://arxiv.org/abs/2201.08718
Artificial intelligence (AI), especially deep learning, requires vast amounts of data for training, testing, and validation. Collecting these data and the corresponding annotations requires the implementation of imaging biobanks that provide access t
Externí odkaz:
http://arxiv.org/abs/2201.08356
Autor:
Afshar, Parnian, Mohammadi, Arash, Plataniotis, Konstantinos N., Farahani, Keyvan, Kirby, Justin, Oikonomou, Anastasia, Asif, Amir, Wee, Leonard, Dekker, Andre, Wu, Xin, Haque, Mohammad Ariful, Hossain, Shahruk, Hasan, Md. Kamrul, Kamal, Uday, Hsu, Winston, Lin, Jhih-Yuan, Rahman, M. Sohel, Ibtehaz, Nabil, Foisol, Sh. M. Amir, Lam, Kin-Man, Guang, Zhong, Zhang, Runze, Channappayya, Sumohana S., Gupta, Shashank, Dev, Chander
Lung cancer is one of the deadliest cancers, and in part its effective diagnosis and treatment depend on the accurate delineation of the tumor. Human-centered segmentation, which is currently the most common approach, is subject to inter-observer var
Externí odkaz:
http://arxiv.org/abs/2201.00458
Privacy-preserving machine learning enables the training of models on decentralized datasets without the need to reveal the data, both on horizontal and vertically partitioned data. However, it relies on specialized techniques and algorithms to perfo
Externí odkaz:
http://arxiv.org/abs/2112.09436