Abstract
In this paper we summarize the results of our analysis of data provided by the Aging and Dementia Research Center (ADRC) at the New York University Medical Center. This database stores a series of results of examinations of thousands of subjects with ostensibly normal brain aging, subjective cognitive impairment, mild cognitive impairment, Alzheimer's disease and related conditions. These investigations were done in the USA over three decades from 1978 to 2008. All patients are classified using the global deterioration scale (GDS). The data have been analyzed statistically; we have developed a statistical model for the expected duration of each GDS period. Additionally, we also used several machine learning techniques in order to identify mathematical models that can be used as estimators for the GDS classification.
| Original language | English |
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| Title of host publication | Proceedings of 21st European Modeling and Simulation Symposium EMSS 2009 |
| Publisher | DIPTEM University of Genova |
| Pages | 167-172 |
| Publication status | Published - 2009 |
| Event | 21st European Modeling and Simulation Symposium, EMSS 2009 - Puerto de la Cruz, Spain Duration: 23 Sept 2009 → 25 Sept 2009 |
Conference
| Conference | 21st European Modeling and Simulation Symposium, EMSS 2009 |
|---|---|
| Country/Territory | Spain |
| City | Puerto de la Cruz |
| Period | 23.09.2009 → 25.09.2009 |
Keywords
- Data mining
- Disease progress modeling
- Morbus Alzheimer
- System identification