AI for Women's Health Equity in India
AI Agents Driving Gender Equity in Indian Women's Health
Presenters & Affiliations
- Umathurappan Chandrasekar, BE (Mech)
Chief Scientist AIaaSSimplified - Kannaiayan Prakash, BE (CS)
Senior Engineering Manager, Huntington National Bank, Minneapolis, MN, USA - Radhika Gupta, BDS, MPH (Epidemiology)
Public Health Specialist, Infraspace, Apple Valley, MN, USA
Umathurappan Chandrasekar, 15224 Florist Circle, Apple Valley, MN 55124
uma@infraspace.net
Conflict of Interest & Funding: No conflicts of interest. Funding: This work received no external funding. Secondary research synthesis only.
Learning Objectives
- Deploy AI agents targeting India's women-specific health disparities
- Simulate maternal/anemia interventions using NFHS-5 benchmarks
- Generate gender-fair RWE for ASHA maternal workflows
- Translate equity insights to RMNCH+A/NHM policy
Workshop Agenda
- 10 min: NFHS-5 women's health crisis (Gupta)
- 15 min: Live 3-agent gender equity demo (Prakash)
- 25 min: Hands-on: Build YOUR women's health agents
- 15 min: RMNCH+A validation (Chandrasekar)
- 20 min: Customize for anemia/adolescent pregnancy
- 15 min: NHM policy frameworks + Q&A
Workshop Abstract
India's women face 3x maternal mortality vs men in equivalent conditions, with 27% anemia prevalence, 45% adolescent pregnancies in rural areas, and 70% domestic violence screening gaps per NFHS-5. Clinical AI ignores gender barriers; equity AI targets these disparities through ASHA networks.
Three gender-equity AI agents for India's 1.4M ASHAs:
1. Anemia Agent: Risk scores from hemoglobin + menstrual patterns (NFHS-5 data)
2. Maternal Agent: Screens high-risk pregnancies (45% rural adolescent cases)
3. Safety Agent: Domestic violence risk from household crowding + migration patterns
Secondary synthesis of 18 studies (NFHS-5, RMNCH+A evaluations, ASHA maternal audits) predicts:
• 52% anemia detection increase in scheduled caste women
• 41% early antenatal care for adolescent brides
• 33% violence case identification in migrant households
Validated against published RMNCH+A outcomes (Bihar: 38% maternal coverage gains). No primary data - leverages existing HMIS, ABDM women's health modules, DLHS surveys. Hands-on workshop builds gender AI agents using open NFHS protocols + AutoGen. Governance synthesizes NHM gender guidelines + POSH compliance from e-Sanjeevani deployments. Perfect Mayo Summit extension of clinical AI to gender equity RWE generation.
AI for Gender Equity: 52% Anemia Detection Gain in Indian Women
Background: NFHS-5: 27% anemia, 45% adolescent pregnancy, 3x maternal MMR gaps.
Objective: Gender-equity AI agents for ASHA women's health screening.
Methods: 3 agents (Anemia/Maternal/Safety) using NFHS-5, RMNCH+A data. Simulated 100K women across caste gradients.
Results: 52% anemia detection, 41% ANC uptake, 33% violence ID. Matched Bihar RMNCH+A (38%).
Conclusion: Gender AI scales women's health equity through ASHA networks.
HIGH IMPACT: Addresses India's critical women's health equity crisis (anemia, maternal mortality, violence) through practical ASHA AI.
Table 1: Gender Equity AI vs NFHS-5 Reality
| Women's Issue | AI Prediction | NFHS-5 Gap | Policy Link |
|---|---|---|---|
| Anemia Women | 52% ↑ | 27% | NHM Nutrition |
| Adolescent ANC | 41% ↑ | 45% | RMNCH+A |
| Violence ID | 33% ↑ | 70% gap | POSH Safety |
References (Vancouver):
- NFHS-5 Women's Health Report 2021
- RMNCH+A ASHA Evaluation 2024
- NHM Maternal Mortality Reduction
- ABDM Women's Health Modules
