Karin Hagoort
Biographic Data
| ID | 7866539 |
|---|---|
| NAME | Karin Hagoort |
| GIVEN NAMES | Karin |
| FAMILY NAME | Hagoort |
| SIGNATURE | HAGOORT K |
| AFFILIATIONS | University Medical Center Utrecht |
| ORCID | 0000-0002-3891-5121 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2018 |
| LATEST PUBLICATION YEAR | 2020 |
| H-INDEX | 0 |
The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions
Major depressive disorder imposes a substantial disease burden worldwide, ranking as the third leading contributor to global disability. In spite of its ubiquity, classifying and treating depression has proven troublesome. One argument put forward to explain this predicament is the heterogeneity of patients diagnosed with the disorder. Recently, many areas of daily life have witnessed the surge of machine learning techniques, computational approa…
Does Residential Green and Blue Space Promote Recovery in Psychotic Disorders? A Cross-Sectional Study in the Province of Utrecht, The Netherlands
Mental health is reportedly influenced by the presence of green and blue space in residential areas, but scientific evidence of a relation to psychotic disorders is scant. We put two hypotheses to the test: first, compared to the general population, psychiatric patients live in neighborhoods with less green and blue space; second, the amount of green and blue space is negatively associated with the duration of hospital admission. The study popula…
No prominent works on this page.
Does Residential Green and Blue Space Promote Recovery in Psychotic Disorders? A Cross-Sectional Study in the Province of Utrecht, The Netherlands
Mental health is reportedly influenced by the presence of green and blue space in residential areas, but scientific evidence of a relation to psychotic disorders is scant. We put two hypotheses to the test: first, compared to the general population, psychiatric patients live in neighborhoods with less green and blue space; second, the amount of green and blue space is negatively associated with the duration of hospital admission. The study popula…
The Predictive Validity of Machine Learning Models in the Classification and Treatment of Major Depressive Disorder: State of the Art and Future Directions
Major depressive disorder imposes a substantial disease burden worldwide, ranking as the third leading contributor to global disability. In spite of its ubiquity, classifying and treating depression has proven troublesome. One argument put forward to explain this predicament is the heterogeneity of patients diagnosed with the disorder. Recently, many areas of daily life have witnessed the surge of machine learning techniques, computational approa…
Depression (economics (2 works) · Medicine (2 works) · Psychiatry (2 works) · Psychology (2 works) · Anxiety (1 works) · Argument (complex analysis (1 works) · Artificial Intelligence (1 works) · Computer Science (1 works) · Confounding (1 works) · Data science (1 works)