Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67156, first published .
Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study

Journals

  1. del Rey Puech P, Payne R, Saund J, McKee M. Mind the (widening) gap: why public health must engage with AI now. Public Health 2026;250:106047 View
  2. Frias M. Methodological reflections on time-series approaches to suicide trends in South Korea. Asian Journal of Psychiatry 2026;115:104774 View