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Generalizable calibrated machine learning models for real-time atrial fibrillation risk prediction in ICU patients
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- Journal Article
- A1
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Pathogen-based target attainment of optimized continuous infusion dosing regimens of piperacillin-tazobactam and meropenem in surgical ICU patients : a prospective single center observational study
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- Conference Paper
- P1
- open access
Powershap : a power-full shapley feature selection method
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- Conference Paper
- open access
Workshops at the Web Conference 2023
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- Journal Article
- A1
- open access
Bridging the gap between expressivity and efficiency in stream reasoning : a structural caching approach for IoT streams
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- Conference Paper
- C1
- open access
Leak localization in water distribution networks by directly fitting the learning parameters of a Gaussian naive Bayes classifier
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- Conference Paper
- C1
- open access
From self-reporting to monitoring for improved migraine management
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- Journal Article
- A1
- open access
Assessing the added value of context during stress detection from wearable data
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- Journal Article
- A1
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mBrain : towards the continuous follow-up and headache classification of primary headache disorder patients
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NAOMI platform optimizes communication with relatives of patients
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- Journal Article
- A1
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An adaptation algorithm for personalised virtual reality exposure therapy
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- Journal Article
- A1
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Hierarchical pattern matching for anomaly detection in time series
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INK : knowledge graph embeddings for node classification
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- Conference Paper
- C1
- open access
Towards knowledge-driven symptom monitoring & trigger detection of primary headache disorders
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- Conference Paper
- C3
- open access
Hybrid machine learning for leak localization in the drinking water grid
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- Conference Paper
- C3
- open access
PowerShap : a power-full Shapley feature selection method
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- Journal Article
- A1
- open access
Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients
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- Journal Article
- A1
- open access
FLAGS : a methodology for adaptive anomaly detection and root cause analysis on sensor data streams by fusing expert knowledge with machine learning
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- Journal Article
- A1
- open access
Event-driven dashboarding and feedback for improved event detection in predictive maintenance applications
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- Journal Article
- A1
- open access
A complete software stack for IoT time-series analysis that combines semantics and machine learning-lessons learned from the dyversify project