Microscopía inteligente: el impacto de la IA en la exploración de lo invisible

Artificial intelligence is transforming microscopy in areas such as medicine and materials science, highlighting the importance of multidisciplinary collaboration to advance the exploration of the invisible. This study presents two cases in point: the first focuses on the analysis of pathology images, demonstrating that it is possible to classify these images using AI algorithms, starting with the selection of the most appropriate microscopic magnification. The second addresses the benefits of material characterization through various AI-based approaches. The integration of knowledge from medicine, engineering and computing not only improves accuracy and efficiency in both fields, but also fosters new research and development strategies. This collaborative approach enables advanced analytical technologies, traditionally limited to a single domain, to be applied in innovative ways to other fields, thus accelerating discovery.