Mining biomedical time series by combining structural analysis and temporal abstractions

By Riccardo Bellazzi, P. Magni, C. Larizza, Giuseppe De Nicolao, A. Riva, M. Stefanelli. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Mahsa Oroojeni Mohammad Javad
2. Stephen Agboola
3. Kamal Jethwani
4. Abe Zeid
5. Sagar V. Kamarthi
6. C. Kaseda
7. Masashi Kobayashi
8. M. Yamaguchi

Citations in the corpus

• A Reinforcement Learning–Based Method for Management of Type 1 Diabetes: Exploratory Study (2019, positive): “Bellazzi et al (1998) used a combination of structural time series analysis and temporal abstraction for interpreting historic blood glucose level to extract and visualize the trends and daily cycles of blood glucose level [16].”
• Prediction of blood glucose level of type 1 diabetics using response surface methodology and data mining (2006, methodology): “Several prediction methods have been proposed using chaos theory [6], data mining [ 1 ], and Bayesian analysis [2].”