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Conceptualising inclusive in inclusive innovations: evidence from the AI-based MedTech for cancer detection in India

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  • Pallavi Joshi
  • Dinar Kale
  • Aravinda Meera Guntupalli
  • David Wield

Abstract

Early detection of cancers is a major challenge in India due to the limited availability and access to early detection modalities in low-resource healthcare settings. Recent artificial intelligence (AI)-driven point-of-care (PoC) medical technology (MedTech) innovations for early detection have shown some signs of bridging this gap. This article has two objectives: first, to contextualize these innovations into the broader health-industrial construct of early detection modalities for cancer in India. For this, we use our novel Inclusive Health Innovation framework to frame adaptation of the scarcity-induced innovation matrix by Srinivas and Sutz. Second, it conceptualizes inclusivity in the context of these PoC MedTechs, exploring its implications for cancer detection in India. Using three case studies of PoC MedTechs for oral, breast, and cervical cancer, and data from online semi-structured interviews, this article provides critical insights into inclusiveness in the development process and outcomes of these innovations in low-resource healthcare settings.

Suggested Citation

  • Pallavi Joshi & Dinar Kale & Aravinda Meera Guntupalli & David Wield, 2026. "Conceptualising inclusive in inclusive innovations: evidence from the AI-based MedTech for cancer detection in India," Science and Public Policy, Oxford University Press, vol. 53(1), pages 131-144.
    • Handle: RePEc:oup:scippl:v:53:y:2026:i:1:p:131-144.
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    File URL: http://hdl.handle.net/10.1093/scipol/scaf081
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