Name
Abstract | ||
|---|---|---|
Assistive technology has the potential to enhance the level of independence of people with dementia, thereby increasing the possibility of supporting home-based care. In general, people with dementia are reluctant to change; therefore, it is important that suitable assistive technologies are selected for them. Consequently, the development of predictive models that are able to determine a person's... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/JBHI.2013.2267549 | IEEE Journal of Biomedical and Health Informatics |
Keywords | Field | DocType |
Predictive models,Assistive technology,Dementia,Prediction algorithms,Informatics,Streaming media | Health care,Telemedicine,Mobile radio,Computer science,Usability,Robustness (computer science),Artificial intelligence,Mobile phone,Classifier (linguistics),Machine learning,Dementia | Journal |
Volume | Issue | ISSN |
18 | 1 | 2168-2194 |
Citations | PageRank | References |
11 | 0.87 | 8 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuai Zhang | 1 | 43 | 9.10 |
| Sally Mcclean | 2 | 1029 | 132.29 |
| Chris D. Nugent | 3 | 1150 | 128.39 |
| Mark P. Donnelly | 4 | 140 | 18.83 |
| Leo Galway | 5 | 103 | 16.86 |
| Bryan W. Scotney | 6 | 670 | 82.50 |
| Ian Cleland | 7 | 98 | 23.12 |