XIV CONGRESO INTERNACIONAL DE PROSPECTORES Y EXPLORADORES DESCUBRIENDO RECURSOS MINERALES PARA UN MUNDO MEJOR 50 The integration of tectonic reconstruction and geochemical analysis has provided valuable insights into the geological evolution and mineralization processes in the Andes. By combining these advances with machine learning algorithms, we propose the development of predictive models for mineral deposit locations. This study leverages recent findings on subduction dynamics, magmatic evolution, and structural controls to enhance the accuracy of geological prospecting tools using artificial intelligence. A sensitivity analysis is incorporated to address uncertainties in tectonic reconstructions and geochemical data, ensuring robust predictions. Additionally, the technical details of AI algorithms and a validation protocol for field applications are outlined to enhance replicability and reliability. This approach aims to créate innovative methodologies for improving exploration efficiency and targeting mineral resources in the Andes and beyond. Integrating Knowledge Advances to Design New Geological Prospecting Tools Using Artificial Intelligence Abstract Bloque I Autores: Juan Pablo Bello Nicolás Molina Sebastián Seguel Nicole Krumm José Gómez Andrés Sandoval Gonzalo Zúñiga Alonso Cancino Francisco Pontigo Rodrigo Riquelme Alejandro Cáceres GeoInnova Consultores DESCARGUE REVISE PAPER
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