03/08/2026
๐๐๐๐ญ ๐ญ๐ก๐ ๐
๐ข๐ง๐๐ฅ๐ข๐ฌ๐ญ๐ฌ ๐จ๐ ๐ญ๐ก๐ ๐๐๐๐ฅ๐ญ๐ก๐๐๐ซ๐ (๐๐๐๐ฅ๐ญ๐ก๐๐๐๐ก) ๐๐จ๐ฆ๐๐ข๐ง ๐๐ญ ๐๐๐ ๐๐๐
๐๐๐๐๐ ๐๐ ๐๐๐๐๐๐
๐๐๐ ๐๐๐๐
Meet ๐๐๐๐ฆ ๐๐๐ฎ๐ซ๐๐ฅ ๐๐จ๐ฆ๐๐๐ฌ, one of the finalists in the Healthcare (HealthTech) Domain, with their project ๐๐๐ญ๐๐ซ๐ง๐๐ฅ ๐๐๐๐ฅ๐ญ๐ก ๐๐จ๐ฆ๐ฉ๐๐ง๐ข๐จ๐ง, powered by their AI-driven maternal healthcare intelligence platform, ๐๐๐ ๐๐ซ๐๐ ๐๐.
๐๐ก๐ ๐๐ซ๐จ๐๐ฅ๐๐ฆ ๐๐ก๐๐ฒ ๐๐๐๐ซ๐๐ฌ๐ฌ๐๐
Maternal mortality and preventable pregnancy complications remain serious healthcare challenges, particularly in rural, remote, and underserved communities.
Many pregnant women do not receive consistent prenatal care because of limited healthcare infrastructure, shortages of specialists, irregular antenatal checkups, fragmented records, geographic barriers, and poor access to reliable maternal-health information.
Without continuous monitoring, conditions such as anemia, hypertension, malnutrition, gestational complications, and high-risk pregnancies may remain undetected until they develop into emergencies.
Healthcare workers also rely heavily on manual processes and delayed reporting, making it difficult to identify vulnerable mothers early and provide preventive interventions.
There is a critical need for an accessible and scalable system that can support early risk detection, continuous monitoring, and informed maternal healthcare decisions.
๐๐ก๐๐ข๐ซ ๐๐จ๐ฅ๐ฎ๐ญ๐ข๐จ๐ง: ๐๐๐ ๐๐ซ๐๐ ๐๐
๐๐๐ ๐๐ซ๐๐ ๐๐ is an integrated maternal healthcare intelligence platform designed to analyse individual and community-level health information before risks escalate.
The platform evaluates:
โข Clinical records and pregnancy history
โข Blood pressure and hemoglobin levels
โข Nutrition indicators and symptoms
โข Behavioural and health-related factors
โข Community trends and population-level risk patterns
Using AI models and clinical scoring systems, it generates:
๐๐ง๐๐ข๐ฏ๐ข๐๐ฎ๐๐ฅ-๐๐๐ฏ๐๐ฅ ๐๐ง๐ญ๐๐ฅ๐ฅ๐ข๐ ๐๐ง๐๐
โข Maternal risk scores
โข Anemia and hypertension risk assessments
โข Nutrition analysis
โข Personalized recommendations
โข Clinical alerts
๐๐จ๐ฆ๐ฆ๐ฎ๐ง๐ข๐ญ๐ฒ-๐๐๐ฏ๐๐ฅ ๐๐ง๐ญ๐๐ฅ๐ฅ๐ข๐ ๐๐ง๐๐
โข Village-level risk analysis
โข Maternal health hotspot detection
โข Forecasted risk trends
โข Population-health monitoring
โข Resource-allocation recommendations
The platform also supports automated intervention planning, knowledge-graph exploration, multi-agent reasoning, risk forecasting, and clinical insight generation.
By combining individual care insights with population-level intelligence, NAB Preg AI aims to help healthcare organizations move from reactive treatment toward proactive maternal-health management.
The system is designed to support healthcare professionals and public-health organizations. It does not replace clinical diagnosis, emergency care, or qualified medical judgment.
Congratulations to ๐๐๐๐ฆ ๐๐๐ฎ๐ซ๐๐ฅ ๐๐จ๐ฆ๐๐๐ฌ for becoming a finalist and developing a meaningful HealthTech solution focused on early detection, preventive intervention, and safer maternal care.
๐๐ก๐๐ญโ๐ฌ ๐๐๐ฑ๐ญ?
Get ready for the next big journey:
๐๐ง๐ญ๐๐ซ๐ง๐๐ญ๐ข๐จ๐ง๐๐ฅ ๐๐ ๐๐ฎ๐ข๐ฅ๐๐๐ซ๐ฌ ๐๐จ๐ง๐ ๐ซ๐๐ฌ๐ฌ ๐๐๐๐
๐ Daffodil International University
๐
Saturday, December 26, 2026 | 7:00 AM
๐๐ฎ๐ข๐ฅ๐ ๐๐ก๐๐ญ ๐๐๐ญ๐ญ๐๐ซ๐ฌ. ๐๐๐๐ฅ๐ ๐๐ก๐๐ญ ๐๐จ๐ซ๐ค๐ฌ. ๐๐ก๐๐ฉ๐ ๐๐ก๐๐ญ ๐๐จ๐ฆ๐๐ฌ ๐๐๐ฑ๐ญ.
๐ ๐๐ฉ๐ฉ๐ฅ๐ฒ ๐๐จ๐ฐ: cloudcampbd.com/ai-builders-congress