AI in Cancer Screening, Significance, Challenges

AI-enabled cervical cancer screening is among 37 Indian deep-tech innovations showcased at the BRICS Bharat Innovates Exposition during the 18th BRICS Summit in New Delhi. The exposition highlights Indian innovations in healthcare, space technology, clean energy and other sectors.

What is AI in Cancer Screening?

AI in cancer screening refers to the use of machine learning and deep learning algorithms to analyse medical images or clinical data and identify patterns that may indicate cancer. AI can support screening by:

• Detecting abnormalities: Identifying suspicious lesions, nodules or masses in medical images.
• Screening and triage: Assessing patients and prioritising those who may require further medical examination.
• Reducing workload: Helping doctors process large volumes of medical images more quickly.
• Supporting early detection: Identifying possible signs of cancer before the disease progresses.
• Improving access: Supporting screening in areas where specialised medical professionals and advanced diagnostic facilities are limited.

AI is generally used as a decision-support or triage tool, rather than as a replacement for doctors.

AI in Cancer Screening at BRICS Bharat Innovates Exposition

The BRICS Bharat Innovates (BBI) Exposition is being held at Bharat Mandapam, New Delhi, on September 11-12, 2026, alongside the 18th BRICS Summit. 

• The exposition is organised by the Ministry of Education in coordination with the Ministry of External Affairs and is aligned with India’s BRICS 2026 theme, “Building for Resilience, Innovation, Cooperation and Sustainability.”
• The BBI Exposition aims to connect Indian startups and innovators with BRICS investors, companies, research institutions and other global stakeholders, creating opportunities for technology partnerships, investment and international market access. 
• It is showcasing 37 Indian deep-tech startups and ventures from areas such as healthcare, clean energy, space technology and advanced manufacturing. 
• Among the innovations showcased is an AI-enabled cervical cancer screening technology, highlighting the use of Indian deep-tech solutions to improve cancer screening and early detection.

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Significance of AI in Cancer Screening

AI is being used across different stages of cancer screening to support early detection, assess risk and improve the screening and referral process.

• Early Detection: AI can identify subtle abnormalities in medical images and screening data, helping detect possible cancer at an earlier stage.
• Risk Assessment: AI can analyse clinical and health data to identify individuals who may have a higher risk of developing cancer and may require further screening.
• Screening: AI can analyse medical images and other screening data to identify patterns that may indicate cancer and support large-scale screening programmes.
• Screening and Triage: AI can identify suspicious cases and help healthcare workers prioritise patients who need further examination or referral.
• Medical Image Analysis: AI can examine mammograms, thermal images and cervical images to detect abnormalities that may require further clinical assessment.
• Referral and Follow-up: AI can support healthcare workers in deciding which patients require further investigation, referral or follow-up after initial screening.
• Clinical Decision Support: AI can assist doctors and healthcare professionals by analysing patient data and providing information that supports clinical decision-making.

Indian examples: Periwinkle Technologies has developed an AI-enabled platform for cervical cancer screening and risk assessment, while Niramai uses radiation-free thermal imaging technology with AI to support early breast cancer detection.

Significance of AI in Cancer Screening for India 

AI-based cancer screening is particularly relevant for India because healthcare infrastructure and specialised medical expertise are unevenly distributed.

In many areas, patients may have limited access to advanced diagnostic facilities and specialists. AI-enabled screening tools can potentially support district-level and primary healthcare facilities by assisting healthcare workers in identifying high-risk cases.

This can help reduce delays between screening, referral and diagnosis, which is important for improving cancer outcomes.

Challenges of AI in Cancer Screening

Despite its potential, AI-based screening also faces several challenges.

• Accuracy: AI systems may not always correctly identify abnormalities, creating the possibility of false results.
• Data limitations: AI systems require large and reliable datasets for training and validation.
• Human oversight: AI recommendations still require appropriate clinical assessment by trained healthcare professionals.
• Infrastructure: Effective deployment requires suitable medical equipment, digital connectivity and trained personnel.
• Accessibility: Advanced technologies may remain concentrated in urban and well-equipped healthcare facilities if their deployment is not planned equitably.
• Clinical validation: AI tools need to be properly tested before being used widely in healthcare.
• Data protection: Medical and health-related information requires appropriate safeguards against misuse and unauthorised access.

Way Forward

India should focus on clinically validating AI tools, improving healthcare infrastructure and ensuring secure health-data systems before large-scale deployment. AI should complement, not replace, healthcare professionals, while greater investment in indigenous solutions, public healthcare integration and equitable access can help extend AI-based cancer screening to underserved areas.