Svitlana Zinger
Biographic Data
| ID | 6462215 |
|---|---|
| NAME | Svitlana Zinger |
| GIVEN NAMES | Svitlana |
| FAMILY NAME | Zinger |
| SIGNATURE | ZINGER S |
| AFFILIATIONS | Eindhoven University of Technology |
| ORCID | 0000-0001-9357-3067 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2009 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 0 |
Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task
The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts
Where are the Search Engines for Handwritten Documents
Although the problems of optical character recognition for contemporary printed text have been resolved, for historical printed and handwritten connected cursive text (i.e. western style writing), they have not. This does not mean that scanning historical documents is not useful. This article describes our research on retrieving digitized handwritten documents containing the information that the user is looking for. This task is essential for opt…
No prominent works on this page.
Where are the Search Engines for Handwritten Documents
Although the problems of optical character recognition for contemporary printed text have been resolved, for historical printed and handwritten connected cursive text (i.e. western style writing), they have not. This does not mean that scanning historical documents is not useful. This article describes our research on retrieving digitized handwritten documents containing the information that the user is looking for. This task is essential for opt…
Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task
The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts
Artificial Intelligence (2 works) · Computer Science (2 works) · Advanced MRI Techniques and Applications (1 work) · Advanced Neuroimaging Techniques and Applications (1 work) · Character (mathematics (1 work) · Cognition (1 work) · Cursive (1 work) · Default mode network (1 work) · Depression (economics (1 work) · Document processing (1 work)