AI Boosts Breast Cancer Detection, But Resistance Remains

AI is increasingly used to improve early breast cancer detection, though concerns over reliability continue to limit its broader adoption in clinical settings, according to experts from UNAM.

"AI should not replace healthcare professionals but enhance their capabilities," said Oscar Pilloni, Researcher at the Institute of Engineering, UNAM, during the seminar, Health 5.0 and Breast Cancer: Artificial Intelligence for Early and Accurate Detection. Pilloni noted that AI offers efficiency gains in diagnostics but warned against misuse or overreliance.

The integration of AI in medical imaging and diagnostics has been shown to support more precise evaluations, enable the design of targeted drug treatments, and reduce healthcare costs. Breast cancer, in particular, remains a pressing public health challenge. In the United States, cases rose from one in 11 people in the 1970s to one in eight by 2019, a trend also seen in Mexico. Globally, 685,000 women died from breast cancer in 2020, making it the second leading cause of cancer death in women after lung cancer.

Rosa María Ramírez, Director of the Institute of Engineering, UNAM, emphasized that the disease requires a collective response involving academia, industry, and government. She underscored the importance of scientific collaboration in leveraging new technologies to address breast cancer, which she called a “painful and costly condition” for patients and their families.

Despite growing interest from the private sector, barriers remain. The global AI in healthcare market was valued at US$14.92 billion in 2024 and is expected to grow 38.6% annually, reaching US$21.66 billion in 2025 and over US$110 billion by 2030. However, adoption in clinical practice remains limited due to skepticism from medical professionals and a shortage of trained personnel in AI-powered software.

Many healthcare workers continue to rely on traditional tools due to perceived unreliability of AI systems and a lack of trust in automated diagnostics. Pilloni stressed the need for ethical deployment and cross-sector cooperation to validate AI's effectiveness and ensure its responsible use in patient care.

Alimay Mora, Representative, MEIK México, highlighted additional structural challenges during a breast palpation workshop held alongside the seminar. She noted that in Mexico, 31,043 breast cancer cases were reported in 2022, with limited diagnostic capacity. The country has only 689 mammography units and 352 certified radiologic technicians, contributing to late diagnoses in 85% of cases.

Breast cancer is the second leading cause of death among women aged 30 to 54 in Mexico. Screening is recommended for women between 20 and 64, yet only 18% of those under 40 undergo regular checks. Early detection significantly increases survival rates, with the progression from stage 0 to 1 taking up to two years, compared to just six months from stage 1 to 4.

Mora Castillo concluded by emphasizing the role of individual responsibility in detection. Regular self-examinations, performed seven to 10 days after menstruation, are a critical tool for identifying early signs of the disease.