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| Título: | STRATUM project: AI-based point of care computing for neurosurgical 3D decision support tools | Autores/as: | Fabelo, Himar León, Raquel Torti, Emanuele Marco, Santiago Badouh, Asaf Verbers, Max Vega, Carlos Santana Núñez, Javier Falevoz, Yann Ramallo Fariña, Yolanda Weis, Christian Wagner, Ana M. Juarez, Eduardo Rial, Claudio Lagares, Alfonso Burstrom, Gustav Leporati, Francesco Jimenez-Roldan, Luis Marenzi, Elisa Cervero, Teresa Moreto, Miquel Danese, Giovanni Zinger, Svitlana Manni, Francesca Álvarez Malé,Maria Luisa Garcia-Bello, Miguel A. Garcia, Lidia Morera, Jesus Pineiro, Juan F. Bairaktari, Chrysanthi Noriega-Ortega, Beatriz Clavo, Bernardino Callicó, Gustavo M. STRATUM Consortium, S. T. R. A. T. U. M. Consortium |
Clasificación UNESCO: | 3314 Tecnología médica | Palabras clave: | System Multimodal Imaging European Project Point-Of-Care Computing Artificial Intelligence, et al. |
Fecha de publicación: | 2025 | Publicación seriada: | Microprocessors and Microsystems | Resumen: | Integrated digital diagnostics are transforming complex surgical procedures, with brain tumour surgery being among the most challenging. STRATUM, a five-year Horizon Europe-funded project, aims to develop an advanced 3D decision support system leveraging real-time multimodal data processing powered by artificial intelligence. A key innovation of STRATUM is its design as an energy-efficient Point-of-Care computing system, seamlessly integrated into neurosurgical workflows. This system will provide surgeons with real-time, AI-driven insights, enhancing decision-making accuracy and efficiency. By optimizing surgical precision and reducing procedure duration, STRATUM is expected to improve patient outcomes while streamlining resource utilization within European healthcare systems. | URI: | https://accedacris.ulpgc.es/handle/10553/139749 | ISSN: | 0141-9331 | DOI: | 10.1016/j.micpro.2025.105157 | Fuente: | Microprocessors And Microsystems[ISSN 0141-9331],v. 116, (Julio 2025) |
| Colección: | Artículos |
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