AI and the Battle Against Breast Cancer in India

 AI and the Battle Against Breast Cancer in India

Empowering UPSC minds with insight into India’s pressing health challenges
📚 By Suryavanshi IAS

📌 Relevance to UPSC

• GS Paper II: Issues related to health, government schemes, health policy.

• GS Paper III: Science & Technology in health, AI and data protection.

• Essay Paper: Role of innovation in inclusive healthcare.

• Ethics: Equity in tech-enabled healthcare and medical privacy.

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⚠️ Breast Cancer: A Global & Indian Public Health Emergency

🌍 Global Statistics (WHO, 2023):

• 2.3 million new breast cancer cases worldwide annually.

• 670,000 deaths due to breast cancer.

• 1 in 6 deaths globally due to cancer.

• ~50% of affected women have no known risk factors beyond being female and over 40.

🇮🇳 India’s Scenario (GLOBOCAN & ICMR, 2022–24):

• Highest number of breast cancer deaths globally: 98,337 fatalities (2022).

• Over 2.5 lakh new cases annually; projected to reach 4.25 lakh/year by 2040 (IARC).

• Mortality-to-incidence ratio: 51.6% — one of the highest globally (vs 19% in high-income countries).

• Urban-rural gap: Late-stage diagnosis in >70% of rural women vs ~50% in urban areas.

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🧠 Understanding the Challenges

1. Late Detection: 60–70% cases diagnosed in Stage III or IV.

2. Poor Awareness: Only 42% of Indian women are breast self-examination aware.

3. Infrastructure Gaps: India has only ~2,000 mammography units for over 68 crore women (15–70 age group).

4. Manpower Crisis: Radiologist-to-population ratio is 1:100,000. WHO recommends 1:10,000.

5. Affordability: Urban mammograms cost ₹1,000–₹3,000, out of reach for BPL families.

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🤖 Artificial Intelligence: Transforming Early Detection

Key Uses:

AI Tool	Description	Impact
Niramai (AI thermal screening)	Uses thermal imaging + ML	Detects tumours 5 years earlier than palpation
iBreastExam	Portable handheld scanner + AI	Reduces screening time to 5–10 minutes
MammoAssist	AI-backed mammogram analysis	Improves detection rate by up to 20%

📈 Real-World Impact:

• A UK trial showed AI catching 20% more cancers with no increase in false positives.

• AI in IVF has enabled cases like the Columbia Fertility STAR project, where AI identified sperm in azoospermic samples.

• AI-powered fetal monitoring in India has shown 82% reduction in stillbirths (Fortis study, 2023).

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🏛️ Government Initiatives & Gaps

Existing Framework:

• NPCDCS (National Programme for Prevention and Control of Cancer, Diabetes, CVD & Stroke)

• AB-HWC (Ayushman Bharat Health & Wellness Centres) aim to screen 30 crore people annually.

• Pradhan Mantri Digital Health Mission (PM-DHM): Promotes digital records for seamless AI application.

Gaps to Address:

• <20% PHCs equipped with cancer screening tools.

• Limited training on AI-enabled diagnostic interpretation among rural healthcare workers.

• No dedicated regulatory policy on AI use in cancer care (as of 2025).

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🔐 Ethics, Equity & Privacy in AI Health Tech

Challenge	Concern
Bias in AI models	Most models trained on Western datasets – poor Indian applicability.
Data Privacy	No comprehensive health data protection law yet (Digital Personal Data Protection Act only partially addresses medical AI).
Consent & Transparency	Patients often unaware their data is used for algorithm training.
Economic Divide	AI tools cost ₹5–20 lakh — unaffordable for most small clinics/NGOs.

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📦 Recommendations for Policy Makers

1. Incorporate AI tools in NPCDCS at the PHC level – pilot it in high-risk districts.

2. Subsidize AI mammography devices via CSR + health startups under Startup India.

3. Train rural radiologists & ASHAs in using AI-enabled handheld screening devices.

4. Enact AI-in-Medicine Guidelines, including ethics, accountability, and consent.

5. Launch Mobile AI Screening Vans – public-private initiative targeting Tier II–III towns.

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🧪 Mains Practice Question

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)

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🧠 UPSC Interview Tip:

If asked about AI in public health, cite:

• Niramai & iBreastExam

• India’s radiologist shortage

• WHO’s Global Breast Cancer Initiative (2021–40)

• PM Digital Health Mission (PM-DHM)

• Role of mobile tech and telemedicine in reaching rural women

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