Mexico Integrates AI for Early Lung Cancer Detection

The National Institute of Respiratory Diseases "Ismael Cosío Villegas" (INER) in Mexico has integrated advanced artificial intelligence software into its medical imaging analysis processes. The goal is to strengthen the early detection of lung cancer and other high-burden respiratory diseases, including tuberculosis, chronic obstructive pulmonary disease (COPD), and pneumonia. Developed in collaboration with AstraZeneca, this technology has been incorporated into the institute's daily clinical practice to assist medical professionals in interpreting chest X-rays, with a future outlook for analyzing CT scans. The AI system is fully integrated into the INER's image viewer (PACS), allowing medical staff to access automated findings immediately without using external platforms or uploading additional files. This integration is particularly relevant given that the institute performs around 24,000 X-rays annually, a volume that reflects the high demand for imaging studies and the need for tools that optimize diagnostic capabilities without replacing clinical judgment. The AI platform detects potential pulmonary abnormalities, such as nodules, and generates interpretative reports in Spanish, facilitating the classification of lesions as higher or lower risk. This automated support enables clinical teams to more accurately determine the need for complementary studies like CT scans and helps to accelerate key clinical decisions, especially in scenarios where early detection is crucial. The adoption of AI strengthens low-dose CT screening programs, particularly for individuals over 50 with a history of smoking, a group at higher risk for developing lung cancer. In this context, AI is established as a strategic tool to expand timely detection capacity, supporting the early identification of lesions that might otherwise go unnoticed in initial stages. As a teaching hospital, INER is also incorporating this technology into its specialist training model, including in areas like pulmonology, thoracic surgery, and radiology. The use of AI in image analysis allows trainee doctors to learn to integrate advanced digital tools as clinical allies, strengthening their diagnostic skills and readiness for increasingly technology-driven medical scenarios. In a second phase, the institute is working on a model to extend this technology to health centers and hospitals in the Tlalpan area, through a stepped-care referral scheme from primary to tertiary levels. This strategy includes training primary care physicians and incorporating the AI software into units equipped with X-ray machines, with the aim of improving the early detection of lung cancer and other respiratory diseases from the initial stages of care. For INER, the implementation of this tool represents a strategic advance in innovation, quality of care, and scientific leadership, with an impact that transcends the institutional sphere and projects into Mexico and Latin America. The integration of AI into image analysis consolidates the institute as a regional benchmark in the adoption of emerging technologies applied to high-specialty respiratory care, with direct benefits for patients, medical staff, and health systems.