Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

MLA

Cearns, Micah, et al. “Using Polygenic Scores and Clinical Data for Bipolar Disorder Patient Stratification and Lithium Response Prediction: Machine Learning Approach.” The British Journal of Psychiatry : The Journal of Mental Science, Feb. 2022, pp. 1–10. EBSCOhost, https://doi.org/10.1192/bjp.2022.28.

APA

Cearns, M., Amare, A. T., Schubert, K. O., Thalamuthu, A., Frank, J., Streit, F., Adli, M., Akula, N., Akiyama, K., Ardau, R., Arias, B., Aubry, J.-M., Backlund, L., Bhattacharjee, A. K., Bellivier, F., Benabarre, A., Bengesser, S., Biernacka, J. M., Birner, A., … Baune, B. T. (2022). Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach. The British Journal of Psychiatry : The Journal of Mental Science, 1–10. https://doi.org/10.1192/bjp.2022.28

Chicago

Cearns, Micah, Azmeraw T Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, et al. 2022. “Using Polygenic Scores and Clinical Data for Bipolar Disorder Patient Stratification and Lithium Response Prediction: Machine Learning Approach.” The British Journal of Psychiatry : The Journal of Mental Science, February, 1–10. doi:10.1192/bjp.2022.28.