{
  "id": 7515,
  "url": "https://arxiv.org/abs/2603.13361v1",
  "title": "BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction",
  "summary": "Functional magnetic resonance imaging (fMRI) enables noninvasive investigation of brain function, while short clinical scan durations, arising from human and non-human factors, usually lead to reduced data quality and limited statistical power for neuroimaging research. In this paper, we propose BrainCast, a novel spatio-temporal forecasting framework specifically tailored for whole-brain fMRI time series forecasting, to extend informative fMRI time series without additional data acquisition. It",
  "authors": "Yunlong Gao, Jinbo Yang, Li Xiao, Haiye Huo, Yang Ji, Hao Wang et al.",
  "category": "research",
  "topics": "healthcare,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-03-09T08:00:59.000Z",
  "fetched_at": "2026-07-14T16:33:16.669Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/7515",
  "original_url": "https://arxiv.org/abs/2603.13361v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}