Automating ARDS Management: A Dynamical Systems Approach
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Citation: Paul Dagum and Adam Galper and Adam Seiver. (1994) Automating ARDS Management: A Dynamical Systems Approach. In Knowledge Systems, AI Laboratory, February,1994.
| Publication inproceedings ( Edit ) | |
| type | InProceedings |
| bibtype | inproceedings |
| Bibtex basics | |
| author | Paul Dagum and Adam Galper and Adam Seiver |
| title | Automating ARDS Management: A Dynamical Systems Approach |
| booktitle | Knowledge Systems, AI Laboratory |
| address | Stanford, CA, USA |
| year | 1994 |
| month | February |
| Bibtex more | |
| note | Medical Computer Science. Presented at AAAI94 Spring Symposium on Artificial Intelligence in Medicine. In AAAI Press Technical Report Series. |
| publisher | AAAI Press |
| Access Paper | |
| abstract | We explore the use of the delay-coordinate-embedding technique to automatically construct and use probability forecast models. The technique offers distinct advantages, including coherent handling of noise and continuous data, over previously explored probability forecast methods (Dagum et al., Uncertain Reasoning and Forecasting)employing Bayesian belief networks. We discuss the relationship between the dynamical systems and the probabilistic reasoning approaches to probability forecasting. Finally, we apply the dynamical systems method to a multivariate time series of physiologic measurements of an infant with adult respiratory distress syndrome(ARDS). |
| KSL Technical Report ID: KSL-94-04 |
Facts about Automating ARDS Management: A Dynamical Systems ApproachRDF feed
| Abstract | We explore the use of the delay-coordinate … We explore the use of the delay-coordinate-embedding technique to automatically construct and use probability forecast models. The technique offers distinct advantages, including coherent handling of noise and continuous data, over previously explored probability forecast methods (Dagum et al., Uncertain Reasoning and Forecasting)employing Bayesian belief networks. We discuss the relationship between the dynamical systems and the probabilistic reasoning approaches to probability forecasting. Finally, we apply the dynamical systems method to a multivariate time series of physiologic measurements of an infant with adult respiratory distress syndrome(ARDS). adult respiratory distress syndrome(ARDS). |
| Address | Stanford, CA, USA + |
| Author | Paul Dagum and Adam Galper and Adam Seiver + |
| Bibtype | inproceedings + |
| Booktitle | Knowledge Systems, AI Laboratory + |
| Has author | Paul Dagum and Adam Galper and Adam Seiver + |
| Has identifier | KSL-94-04 + |
| Has publishing details | February,1994 + |
| Has title | Automating ARDS Management: A Dynamical Systems Approach + |
| Has where published | Knowledge Systems, AI Laboratory + |
| Has year | 1994 + |
| Ksl tr id | KSL-94-04 + |
| Month | February + |
| Note | Medical Computer Science. Presented at AAAI94 Spring Symposium on Artificial Intelligence in Medicine. In AAAI Press Technical Report Series. |
| Process note | NO + |
| Publisher | AAAI Press + |
| Title | Automating ARDS Management: A Dynamical Systems Approach + |
| Year | 1994 + |
