Context:

Recently, AIIMS Delhi has invented an AI-enabled device that can identify breast cancer patterns specific to Indian women. 

More on the News

• This initiative is part of an ambitious project by AIIMS Delhi aimed at improving early breast cancer detection and reducing mortality, which remains among the highest globally.
• The project is one of the first under the government’s flagship scheme to establish three Centres of Excellence (CoE) in AI, focusing on healthcare, agriculture, and sustainable cities.

Key Highlights of Initiative

• The goal of the initiative is to eventually integrate this AI screening tool into India’s national health program, allowing ASHA workers to use it for breast cancer detection.
• The Device works in tandem with ASHA workers, who will collect health and family disease data using a certain set of questions, which will get updated and refined over time. 
• These vital data will be fed into the AI tool to identify breast cancer risk factors, recommend mammograms (specialized X-rays for early detection), and define no-risk categories. 
• The use of AI will not disrupt current treatment methods. There will also be expert oversight to ensure the system works effectively.
• In this initiative, data security will be a top priority. All personal health data will be securely encrypted.

Working of the AI tool

• The AI model will first learn from a large database of women tested for breast cancer at AIIMS, NCI Jhajjar, and PGI Chandigarh to predict breast cancer risk by combining test results, lifestyle, and family history data.
• In the second phase, AI will analyze mammograms, recognizing complex cancer indicators without requiring on-site radiologists, thus reducing costs and increasing accessibility.
• By enabling less-trained personnel to interpret mammograms with AI assistance, the initiative aims to expand screening coverage and lower breast cancer mortality, which accounts for 10.6% of cancer deaths in India.

Significance of the Tool

• The AI tool enables early breast cancer detection by identifying high-risk women for mammograms and reassuring low-risk individuals, promoting timely screening.
• It accurately reads mammograms, supporting advanced cancer screening in remote areas with limited radiologists, and reducing diagnostic delays.