Breast cancer

 Q. Breast cancer is becoming a major non-communicable disease burden in India. Examine how artificial intelligence can enhance early detection and treatment. Discuss the ethical and infrastructural challenges involved in integrating AI into public healthcare.

(250 words)

Breast cancer has emerged as the most common cancer among Indian women, accounting for over 2.5 lakh new cases annually, with a mortality-to-incidence ratio of 51.6%, largely due to late detection and poor accessibility to diagnostic services. Artificial Intelligence (AI) offers significant promise in transforming early detection and personalised treatment.

AI-powered tools such as Niramai (thermal imaging) and iBreastExam (handheld scanners) enable non-invasive, cost-effective, and accurate early screening. These technologies can detect tumours even before physical symptoms appear, increasing the chances of survival. AI can also assist in mammogram interpretation, identify high-risk patients, and support treatment decisions through predictive modelling and analysis of patient data. It is especially useful in India, where the radiologist-to-population ratio is alarmingly low (1:100,000).

However, integration of AI in public health systems faces challenges. Infrastructure gaps such as inadequate electricity, poor internet connectivity, and lack of mammography machines in Primary Health Centres (PHCs) limit AI implementation. Additionally, AI models are often trained on non-Indian datasets, reducing diagnostic accuracy for Indian patients.

Ethically, data privacy is a major concern, as AI requires access to sensitive medical information. Without stringent regulations or patient consent protocols, there is a risk of data misuse. Furthermore, AI cannot replace clinical empathy or human judgment, making its use complementary, not substitutive.

In conclusion, while AI can revolutionise breast cancer detection and treatment in India, responsible integration requires robust infrastructure, ethical safeguards, and human oversight.