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IHI
2010
132views Healthcare» more  IHI 2010»
13 years 2 months ago
Section classification in clinical notes using supervised hidden markov model
As more and more information is available in the Electronic Health Record in the form of free-text narrative, there is a need for automated tools, which can process and understand...
Ying Li, Sharon Lipsky Gorman, Noemie Elhadad
ICML
2010
IEEE
13 years 8 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
ICIP
2007
IEEE
13 years 7 months ago
Robust Multi-Modal Group Action Recognition in Meetings from Disturbed Videos with the Asynchronous Hidden Markov Model
The Asynchronous Hidden Markov Model (AHMM) models the joint likelihood of two observation sequences, even if the streams are not synchronised. We explain this concept and how the...
Marc Al-Hames, Claus Lenz, Stephan Reiter, Joachim...
AIRS
2006
Springer
13 years 9 months ago
Text Mining for Medical Documents Using a Hidden Markov Model
Abstract. We propose a semantic tagger that provides high level concept information for phrases in clinical documents. It delineates such information from the statements written by...
Hyeju Jang, Sa-Kwang Song, Sung-Hyon Myaeng
PE
2002
Springer
124views Optimization» more  PE 2002»
13 years 7 months ago
Continuous-time hidden Markov models for network performance evaluation
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the...
Wei Wei, Bing Wang, Donald F. Towsley