Predictive models for pressure ulcers from intensive care unit electronic health records using Bayesian networks
P Kaewprag, C Newton, B Vermillion, S Hyun… - BMC medical informatics …, 2017 - Springer
Background We develop predictive models enabling clinicians to better understand and
explore patient clinical data along with risk factors for pressure ulcers in intensive care unit …
explore patient clinical data along with risk factors for pressure ulcers in intensive care unit …
Mobile cloud-based depression diagnosis using an ontology and a Bayesian network
Recently, depression has becomes a widespread disease throughout the world. However,
most people are not aware of the possibility of becoming depressed during their daily lives …
most people are not aware of the possibility of becoming depressed during their daily lives …
[PDF][PDF] Resident space object characterization and behavior understanding via machine learning and ontology-based bayesian networks
In this paper, we present an end-to-end approach that employs machine learning
techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of …
techniques and Ontology-based Bayesian Networks (BN) to characterize the behavior of …
Integrating ontological modelling and Bayesian inference for pattern classification in topographic vector data
P Lüscher, R Weibel, D Burghardt - Computers, Environment and Urban …, 2009 - Elsevier
This paper presents an ontology-driven approach for spatial database enrichment in support
of map generalisation. Ontology-driven spatial database enrichment is a promising means to …
of map generalisation. Ontology-driven spatial database enrichment is a promising means to …
Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks
Several studies have described the prevalence and severity of diagnostic errors. Diagnostic
errors can arise from cognitive, training, educational and other issues. Examples of cognitive …
errors can arise from cognitive, training, educational and other issues. Examples of cognitive …
Combining ontology and probabilistic models for the design of bio-based product transformation processes
This paper presents a workflow for the design of transformation processes using different
kinds of expert's knowledge. It introduces POND (Process and observation ONtology …
kinds of expert's knowledge. It introduces POND (Process and observation ONtology …
Extending the range of symptoms in a Bayesian Network for the Predictive Diagnosis of COVID-19
R Butcher, N Fenton - medRxiv, 2020 - medrxiv.org
Emerging digital technologies have taken an unprecedented position at the forefront of
COVID-19 management. This paper extends a previous Bayesian network designed to …
COVID-19 management. This paper extends a previous Bayesian network designed to …
[PDF][PDF] Clinical decision support system based on fuzzy cognitive maps
Decision making in the field of medical diagnosis involves a degree of uncertainty and a
need to take into account the patient's clinical parameters, the context of illness and the …
need to take into account the patient's clinical parameters, the context of illness and the …
Development of context aware system based on Bayesian network driven context reasoning method and ontology context modeling
KE Ko, KB Sim - 2008 International Conference on Control …, 2008 - ieeexplore.ieee.org
Uncertainty of result of context awareness always exists in any context-awareness
computing. This falling-off in accuracy of context awareness result is mostly caused by the …
computing. This falling-off in accuracy of context awareness result is mostly caused by the …
Ontology-based generation of object oriented bayesian networks
Probabilistic Graphical Models (PGMs) are powerful tools for representing and reasoning
under uncertainty. Although useful in several domains, PGMs suffer from their building …
under uncertainty. Although useful in several domains, PGMs suffer from their building …