Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data

Journal article

S. de Wit, T. B. Ziermans, M. Nieuwenhuis, P. F. Schothorst, H. van Engeland, R. S. Kahn, S. Durston, H. G. Schnack
Human Brain Mapping, vol. 38, 2017 Feb, pp. 704-714

DOI: 10.1002/hbm.23410

Cite

APA Click to copy
de Wit, S., Ziermans, T. B., Nieuwenhuis, M., Schothorst, P. F., van Engeland, H., Kahn, R. S., … Schnack, H. G. (2017). Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data. Human Brain Mapping, 38, 704–714. https://doi.org/10.1002/hbm.23410

Chicago/Turabian Click to copy
Wit, S. de, T. B. Ziermans, M. Nieuwenhuis, P. F. Schothorst, H. van Engeland, R. S. Kahn, S. Durston, and H. G. Schnack. “Individual Prediction of Long-Term Outcome in Adolescents at Ultra-High Risk for Psychosis: Applying Machine Learning Techniques to Brain Imaging Data.” Human Brain Mapping 38 (February 2017): 704–714.

MLA Click to copy
de Wit, S., et al. “Individual Prediction of Long-Term Outcome in Adolescents at Ultra-High Risk for Psychosis: Applying Machine Learning Techniques to Brain Imaging Data.” Human Brain Mapping, vol. 38, Feb. 2017, pp. 704–14, doi:10.1002/hbm.23410.

BibTeX Click to copy

@article{de2017a,
  title = {Individual prediction of long-term outcome in adolescents at ultra-high risk for psychosis: Applying machine learning techniques to brain imaging data},
  year = {2017},
  month = feb,
  journal = {Human Brain Mapping},
  pages = {704-714},
  volume = {38},
  doi = {10.1002/hbm.23410},
  author = {de Wit, S. and Ziermans, T. B. and Nieuwenhuis, M. and Schothorst, P. F. and van Engeland, H. and Kahn, R. S. and Durston, S. and Schnack, H. G.},
  month_numeric = {2}
}