Ghent University Academic Bibliography

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Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks

Tom Van Steenkiste (UGent) , Joeri Ruyssinck (UGent) , Leen De Baets (UGent) , Johan Decruyenaere (UGent) , Filip De Turck (UGent) , Femke Ongenae (UGent) and Tom Dhaene (UGent)

(2019) ARTIFICIAL INTELLIGENCE IN MEDICINE. 97. p.38-43
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- A1
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Random survival forests for predicting the bed occupancy in the intensive care unit

Joeri Ruyssinck (UGent) , Joachim van der Herten (UGent) , Rein Houthooft (UGent) , Femke Ongenae (UGent) , Ivo Couckuyt (UGent) , Bram Gadeyne (UGent) , Kirsten Colpaert (UGent) , Johan Decruyenaere (UGent) , Filip De Turck (UGent) and Tom Dhaene (UGent)

(2016) COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE.
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Early detection of positive blood cultures using recurrent neural networks on time series data

Thomas Peiffer, Joeri Ruyssinck (UGent) , Johan Decruyenaere (UGent) , Filip De Turck (UGent) , Femke Ongenae (UGent) and Tom Dhaene (UGent)

(2016) Proceedings of Benelearn 2016.
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Positive blood culture detection in time series data using a BiLSTM network

Leen De Baets (UGent) , Joeri Ruyssinck (UGent) , Thomas Peiffer, Filip De Turck (UGent) , Femke Ongenae (UGent) , Tom Dhaene (UGent) and Johan Decruyenaere (UGent)

(2016) NIPS 2016 Workshop on Machine Learning for Health, Papers.
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Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores

Rein Houthooft (UGent) , Joeri Ruyssinck (UGent) , Joachim van der Herten (UGent) , Sean Stijven (UGent) , Ivo Couckuyt (UGent) , Bram Gadeyne (UGent) , Femke Ongenae (UGent) , Kirsten Colpaert (UGent) , Johan Decruyenaere (UGent) , Tom Dhaene (UGent) , et al.

(2015) ARTIFICIAL INTELLIGENCE IN MEDICINE. 63(3). p.191-207
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- C3
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Digital Dr. House: A semantic alerting platform for the ICU

Femke Ongenae (UGent) , Bram Gadeyne (UGent) , Femke De Backere (UGent) , L De BUs, P Depuydt, Johan Decruyenaere (UGent) and Filip De Turck (UGent)

(2015) Semantic Web Applications and Tools for Life Sciences International Conference. p.1-2
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Probabilistic priority assessment of nurse calls

Femke Ongenae (UGent) , Dries Myny (UGent) , Tom Dhaene (UGent) , Tom Defloor (UGent) , Dirk Van Goubergen, Piet Verhoeve, Johan Decruyenaere (UGent) and Filip De Turck (UGent)

(2014) MEDICAL DECISION MAKING. 34(4). p.485-502
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Time series classification for the prediction of dialysis in critically ill patients using echo state networks

Femke Ongenae (UGent) , Stijn Van Looy (UGent) , David Verstraeten (UGent) , Thierry Verplancke, Dominique Benoit (UGent) , Filip De Turck (UGent) , Tom Dhaene (UGent) , Benjamin Schrauwen (UGent) and Johan Decruyenaere (UGent)

(2013) ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE. 26(3). p.984-996
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An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

Femke Ongenae (UGent) , Dries Myny (UGent) , Tom Dhaene (UGent) , Tom Defloor (UGent) , Dirk Van Goubergen (UGent) , Piet Verhoeve, Johan Decruyenaere (UGent) and Filip De Turck (UGent)

(2011) BMC HEALTH SERVICES RESEARCH. 11.
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Design of a probabilistic ontology-based clinical decision support system for classifying temporal patterns in the ICU: a sepsis case study

Femke Ongenae (UGent) , Tom Dhaene (UGent) , Filip De Turck (UGent) , DOMINIQUE BENOIT (UGent) and Johan Decruyenaere (UGent)

(2010) Computer-Based Medical Systems, 23rd IEEE International symposium, Proceedings.

Academic Bibliography

Accurate prediction of blood culture outcome in the intensive care unit using long short-term memory neural networks

Random survival forests for predicting the bed occupancy in the intensive care unit

Early detection of positive blood cultures using recurrent neural networks on time series data

Positive blood culture detection in time series data using a BiLSTM network

Predictive modelling of survival and length of stay in critically ill patients using sequential organ failure scores

Digital Dr. House: A semantic alerting platform for the ICU

Probabilistic priority assessment of nurse calls

Time series classification for the prediction of dialysis in critically ill patients using echo state networks

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

Design of a probabilistic ontology-based clinical decision support system for classifying temporal patterns in the ICU: a sepsis case study

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