An artificial intelligence model developed by Raúl Castro Ortega, a researcher at the Polytechnic University of Tulancingo, manages to identify breast cancer with an accuracy of 90%. The results were presented during the SPIE Photonics Europe 2026 International Congress, in Strasbourg, France.
How the system works
The system uses convolutional neural networks with attention mechanisms to analyze breast thermographs. Unlike traditional methods, the model autonomously learns the patterns of healthy and diseased tissue, without a specialist previously defining the characteristics of the images. This reduces processing time and improves consistency of results.
The study, titled “Breast thermography analysis using convolutional neural networks with attention mechanisms,” uses an algorithm based on the heat diffusion equation. This approach focuses analysis on thermogram regions of interest and classifies tissues with high levels of sensitivity and specificity.
Impact on early detection
The accuracy achieved represents a significant advance for the early detection of breast cancer, which can improve survival rates and facilitate timely treatment. The researcher highlighted that the system does not replace the specialist, but rather works as a support tool for faster and more consistent diagnoses.




