Mexican Researcher Presents AI-Powered Breast Cancer Detection with 90% Accuracy in France

Mexican researcher Raúl Castro Ortega has presented a groundbreaking study in France that utilizes artificial intelligence to detect breast cancer with remarkable accuracy. His model, developed at the Polytechnic University of Tulancingo, achieves up to 90% precision by automatically analyzing thermal images.

The system employs advanced convolutional neural networks with attention mechanisms. Unlike conventional methods that require specialists to pre-define image characteristics, Ortega's model autonomously learns patterns associated with both healthy and diseased breast tissue. This autonomous learning significantly reduces processing time and enhances the reliability of the findings.

Ortega presented his findings at the SPIE Photonics Europe 2026 Congress in Strasbourg, France. The study, titled “Analysis of breast thermography using convolutional neural networks with attention mechanisms,” leverages a heat diffusion equation-based algorithm. This algorithm focuses the analysis on crucial regions within thermograms, enabling the system to classify tissues with high sensitivity and specificity.

This development holds significant promise for early breast cancer detection, offering a potentially faster and more consistent diagnostic tool. The AI's ability to independently identify subtle patterns could lead to earlier interventions and improved patient outcomes.