Published on in Vol 8, No 7 (2020): July
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/17119, first published
.
Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning
Applicability of an Automated Model and Parameter Selection in the Prediction of Screening-Level PTSD in Danish Soldiers Following Deployment: Development Study of Transferable Predictive Models Using Automated Machine Learning
Journals
- Nissen L, Tsamardinos I, Eskelund K, Gradus J, Andersen S, Karstoft K. Forecasting military mental health in a complete sample of Danish military personnel deployed between 1992-2013. Journal of Affective Disorders 2021;288:167 View
- Tsamardinos I, Charonyktakis P, Papoutsoglou G, Borboudakis G, Lakiotaki K, Zenklusen J, Juhl H, Chatzaki E, Lagani V. Just Add Data: automated predictive modeling for knowledge discovery and feature selection. npj Precision Oncology 2022;6(1) View
- Karstoft K, Eskelund K, Gradus J, Andersen S, Nissen L. Early prediction of mental health problems following military deployment: Integrating pre- and post-deployment factors in neural network models. Journal of Psychiatric Research 2023;163:109 View
- Thomaidis G, Papadimitriou K, Michos S, Chartampilas E, Tsamardinos I. A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning. IBRO Neuroscience Reports 2023;15:77 View