Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Dürichen P."'
Autor:
Parsons, Owen, Barlow, Nathan E, Baxter, Janie, Paraschin, Karen, Derix, Andrea, Hein, Peter, Dürichen, Robert
The availability of large and deep electronic healthcare records (EHR) datasets has the potential to enable a better understanding of real-world patient journeys, and to identify novel subgroups of patients. ML-based aggregation of EHR data is mostly
Externí odkaz:
http://arxiv.org/abs/2208.01607
Autor:
Wallis, Jamie, Azqueta-Gavaldon, Andres, Ananthakumar, Thanusha, Dürichen, Robert, Albergante, Luca
Biomedical research is increasingly employing real world evidence (RWE) to foster discoveries of novel clinical phenotypes and to better characterize long term effect of medical treatments. However, due to limitations inherent in the collection proce
Externí odkaz:
http://arxiv.org/abs/2203.07124
Autor:
Javer, Avelino, Parsons, Owen, Carr, Oliver, Baxter, Janie, Diedrich, Christian, Elçi, Eren, Schaper, Steffen, Coboeken, Katrin, Dürichen, Robert
Electronic healthcare records are an important source of information which can be used in patient stratification to discover novel disease phenotypes. However, they can be challenging to work with as data is often sparse and irregularly sampled. One
Externí odkaz:
http://arxiv.org/abs/2112.07239
The increase in availability of longitudinal electronic health record (EHR) data is leading to improved understanding of diseases and discovery of novel phenotypes. The majority of clustering algorithms focus only on patient trajectories, yet patient
Externí odkaz:
http://arxiv.org/abs/2111.06152
Autor:
Carr, Oliver, Jovanovic, Stojan, Albergante, Luca, Andreotti, Fernando, Dürichen, Robert, Lipunova, Nadia, Baxter, Janie, Khan, Rabia, Irving, Benjamin
Determining phenotypes of diseases can have considerable benefits for in-hospital patient care and to drug development. The structure of high dimensional data sets such as electronic health records are often represented through an embedding of the da
Externí odkaz:
http://arxiv.org/abs/2012.13233
Autor:
Andreotti, Fernando, Heldt, Frank S., Abu-Jamous, Basel, Li, Ming, Javer, Avelino, Carr, Oliver, Jovanovic, Stojan, Lipunova, Nadezda, Irving, Benjamin, Khan, Rabia T., Dürichen, Robert
In this work, we propose a multi-task recurrent neural network with attention mechanism for predicting cardiovascular events from electronic health records (EHRs) at different time horizons. The proposed approach is compared to a standard clinical ri
Externí odkaz:
http://arxiv.org/abs/2007.08491
Autor:
Bensch W., Dürichen P.
Publikováno v:
Zeitschrift für Kristallographie - New Crystal Structures, Vol 212, Iss 1, Pp 95-96 (1997)
Externí odkaz:
https://doaj.org/article/51517a5250994308914f1aebafe0872b
Autor:
Bensch W., Dürichen P.
Publikováno v:
Zeitschrift für Kristallographie - New Crystal Structures, Vol 212, Iss JG, Pp 97-98 (1997)
Externí odkaz:
https://doaj.org/article/0659877eef954be4bb60b3a91637ba33
For the efficient execution of deep convolutional neural networks (CNN) on edge devices, various approaches have been presented which reduce the bit width of the network parameters down to 1 bit. Binarization of the first layer was always excluded, a
Externí odkaz:
http://arxiv.org/abs/1812.03410
Affect recognition aims to detect a person's affective state based on observables, with the goal to e.g. provide reasoning for decision making or support mental wellbeing. Recently, besides approaches based on audio, visual or text information, solut
Externí odkaz:
http://arxiv.org/abs/1811.08854