Conceptualising inclusive in inclusive innovations

Evidence from the AI-based MedTech for cancer detection in India

Bibliographic Data

ID17600374
AuthorsPallavi Joshi (0000-0002-5888-3921, The Open University, corresponding author), Dinar Kale (0000-0002-2704-0542, The Open University), A M Guntupalli (0000-0002-4879-2110, University of Aberdeen), David Wield (0000-0003-3838-3724, The Open University)
Year2025
Volume53
Issue1
Pages131-144
Publication date2025-11-18
Open AccessYes
TypeARTICLE
VenueScience and Public Policy (JOURNAL)
Journal identifiersISSN: 0302-3427 • E-ISSN: 1471-5430
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1093/scipol/scaf081
OpenAlexW7130310255
LanguageEN
References cited28

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

Cancer detection · Modalities · Global Health and Surgery · ICT in Developing Communities · Mobile Health and mHealth Applications

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