Qure.ai Partners with THSTI to Develop AI-enabled Ultrasound Tools for Preterm Birth Risk Detection

The partnership forms a part of the GARBH-INi-AnandiMaa initiative, a programme focused on improving outcomes related to preterm births in India

Digital Healthtech innovator Qure.ai has announced a partnership with Translational Health Science and Technology Institute (THSTI) to advance the use of AI in ultrasound imaging for maternal healthcare.

The partnership forms a part of the GARBH-INi-AnandiMaa initiative, a programme focused on improving outcomes related to preterm births in India.

Preterm birth remains a major public health concern globally, contributing significantly to neonatal mortality and long-term health complications, with India accounting for a substantial share of these cases.

The GARBH-INi programme, led by India’s Department of Biotechnology, is designed to address this gap through indigenous research tailored to Indian populations.

The initiative focuses on developing indigenous, data-driven solutions, including AI-based predictive models, to enable earlier detection and intervention.

The programme has reportedly enrolled 12,000 pregnant women and generated over one million ultrasound images to study preterm birth risk factors in the Indian population.

As a part of the collaboration, Qure.ai will provide AI-enabled tools designed to automate ultrasound reporting and enable risk stratification. These tools are expected to assist clinicians in identifying high-risk pregnancies at an earlier stage and generating an actionable risk score.

As per the announcement, the models are being developed using data derived from Indian populations, which is expected to improve their clinical relevance and applicability across diverse healthcare settings.

By developing predictive tools grounded in Indian data, Indian biology, and Indian healthcare realities, the collaboration seeks to reduce the risk associated with preterm birth.

Additionally, the initiative seeks to address gaps in access to specialised diagnostic expertise, particularly in low-resource and non-urban settings where advanced diagnostic services remain limited.

By integrating AI into ultrasound workflows, the initiative aims to support healthcare providers in interpreting imaging data more efficiently and consistently.

Earlier this year, the global healthcare innovator secured a major grant from the Gates Foundation to advance the development of AI-enabled point-of-care ultrasound tools and the creation of a large open-source multimodal database to advance future prevention and identification innovations.

Stay tuned for more such updates on Digital Health News