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Joshi, Pallavi
(2025).
DOI: https://doi.org/10.1093/scipol/scae071
Abstract
Cancer detection poses significant challenges in low-resource healthcare settings, particularly as conventional methods like mammography and Pap smear tests are tailored to the needs of industrialized nations. In recent years, the Indian MedTech sector has witnessed a new trajectory of artificial intelligence– and machine learning–driven innovations that aim to address unmet needs and challenges associated with early cancer detection in such settings. This paper examines the institutional bundles that shape innovation capacity and production capabilities within the MedTech ecosystem and foster the problem-framing and problem-solving of unmet needs of early cancer detection in India. Employing a novel Inclusive Health Innovation framework and 75 years of policy evolution, along with online stakeholder interviews in India, this paper identifies and analyses actors, networks, and knowledge and technology driving these inclusive innovation efforts. The findings of this paper provide lessons for low-resource healthcare settings utilizing emerging technologies for enhanced healthcare access.