Health Data & AI

Data and AI-driven public health responses to endemic, epidemic and climate-related threats

COVID-19 forced an unprecedented level of collaboration between government and researchers/innovators in data science, especially in computational epidemiology (predictions, hospital beds/ICUs planning, lockdown planning, sero-surveillance, wastewater surveillance, genomic surveillance, etc).

In an effort to sustain such collaboration beyond COVID, ARTPARK has created a system where leading computational epidemiology groups (IISc, ISI, ICTS/TIFR, IMD, Indian Institute for Tropical Meteorology, Ashoka, IIIT Delhi, Northeastern, etc.) are addressing the challenges of multiple geographies.

We work closely with the city, state, and national governments to support data-driven public health responses to endemic, epidemic and climate-related threats. We work through a close-coupled implementation and innovation mechanism towards concrete solutions in an open-innovation ecosystem, leveraging various statistical and AI/ML based approaches.

Systems Resilience for Health & Climate

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Heatwaves + Health Risk Prediction

AI-Powered Localized Risk Forecasting Systems for Climate Change and Human Health

Livestock Disease Vaccination Strategy

Disease prevention and control measures to safeguard India’s livestock sector

Dengue Outbreak Prediction

Analytics platform and sub-district level risk prediction for Dengue

GenAI for Health

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Conversational Q&A for Mothers

Our Q&A bot will provide on-demand, real-time, accurate, actionable and personalised information on pregnancy and infant care in an effort to improve health-seeking behaviour that could lead to reduced maternal and child mortality and morbidity.

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Conversational Assistant for Frontline Health Workers

We are building an LLM-based assistant to support workers in accessing timely, accurate and actionable medical knowledge and guidance while training for and managing high-risk pregnancies.

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BellonggAI

Billions of people in LMICs with marginalized identities (gender, caste, disability, sexual orientation, ethnicity, religion) face suboptimal outcomes due to bias and poorly designed programs/policies that ignore their unique needs. These intersectional considerations are often overlooked in SDG activities, leaving gaps in addressing their needs.

BelonggAI and ARTPARK are developing an LLM-based tool to help development practitioners, funders, and researchers uncover and address these exclusions and make their work more inclusive of marginalized groups.

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