
From February 24 to 27, 2026, the International Symposium on Mathematical Methods Applied to the Sciences (SIMMAC) 2026 brought together around 200 participants from more than ten countries, highlighting its strong international and interdisciplinary scope across fields such as Statistics, Data Science, and Applied Mathematics.
Representing Intego Clinical, the study:
“Evaluation of Mixed-Precision Deep Learning for Pneumonia Detection Using GoogLeNet on Chest Radiographs”
was presented by Bernal Aragon and Moises Rodriguez, both Costa Rica–based Statistical Programmers from our San José office.
While this was an independent academic initiative, it is a true point of pride for Intego Clinical to be represented by such exceptional talent. Their participation reflects not only individual excellence, but also the strength, curiosity, and innovation that define our global team.
Advancing AI Efficiency in Medical Imaging
The project explored the use of deep learning for pneumonia detection in chest X-rays, comparing:
Leveraging GoogLeNet and transfer learning in PyTorch, the study evaluated both predictive performance and computational efficiency – an increasingly critical balance in modern healthcare AI.
The results were highly encouraging:
Despite a small difference in accuracy, mixed precision delivered meaningful gains in speed and resource efficiency, reinforcing its value as a scalable and practical solution, especially in environments with limited computational capacity.
A Meaningful Step Forward
Beyond the technical achievements, participation in SIMMAC 2026 represents an important milestone in professional growth, collaboration, and global engagement. Presenting in an international forum, exchanging ideas with researchers, and contributing to discussions at the intersection of mathematics, data science, and healthcare are experiences that continue to elevate both individual and organizational excellence.
At Intego Clinical, we are proud to support and celebrate the achievements of our team members. Their work exemplifies our commitment to innovation, continuous learning, and delivering impactful, data-driven solutions that advance healthcare worldwide