{"ID":2856802,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.10640","arxiv_id":"2510.10640","title":"Equity-Aware Geospatial AI for Forecasting Demand-Driven Hospital Locations in Germany","abstract":"This paper presents EA-GeoAI, an integrated framework for demand forecasting and equitable hospital planning in Germany through 2030. We combine district-level demographic shifts, aging population density, and infrastructure balances into a unified Equity Index. An interpretable Agentic AI optimizer then allocates beds and identifies new facility sites to minimize unmet need under budget and travel-time constraints. This approach bridges GeoAI, long-term forecasting, and equity measurement to deliver actionable recommendations for policymakers.","short_abstract":"This paper presents EA-GeoAI, an integrated framework for demand forecasting and equitable hospital planning in Germany through 2030. We combine district-level demographic shifts, aging population density, and infrastructure balances into a unified Equity Index. An interpretable Agentic AI optimizer then allocates beds...","url_abs":"https://arxiv.org/abs/2510.10640","url_pdf":"https://arxiv.org/pdf/2510.10640v1","authors":"[\"Piyush Pant\",\"Marcellius William Suntoro\",\"Ayesha Siddiqua\",\"Muhammad Shehryaar Sharif\",\"Daniyal Ahmed\"]","published":"2025-10-12T14:51:28Z","proceeding":"cs.AI","tasks":"[\"cs.AI\"]","methods":"[]","has_code":false}