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Interdisciplinary research unlocking innovative solutions in healthcare

Author

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  • Lepore, Dominique
  • Dolui, Koustabh
  • Tomashchuk, Oleksandr
  • Shim, Heereen
  • Puri, Chetanya
  • Li, Yuan
  • Chen, Nuoya
  • Spigarelli, Francesca

Abstract

Advances in Internet of Things (IoT) devices and in Machine Learning (ML) applications can provide valuable insights and predictions on personal health by optimizing data generation and processing.

Suggested Citation

  • Lepore, Dominique & Dolui, Koustabh & Tomashchuk, Oleksandr & Shim, Heereen & Puri, Chetanya & Li, Yuan & Chen, Nuoya & Spigarelli, Francesca, 2023. "Interdisciplinary research unlocking innovative solutions in healthcare," Technovation, Elsevier, vol. 120(C).
    • Handle: RePEc:eee:techno:v:120:y:2023:i:c:s016649722200058x
    DOI: 10.1016/j.technovation.2022.102511
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    References listed on IDEAS

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    Cited by:

    1. Mohammad Daradkeh, 2023. "Exploring the Curvilinear Relationship between Academic-Industry Collaboration Environment and Innovation Performance: A Multilevel Perspective," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    2. Marinelli, Luca & Crupi, Antonio & Del Sarto, Nicola & Lepore, Dominique, 2024. "Unveiling knowledge ecosystem dimensions for MSMEs’ digital transformation, toward a location-based brokerage," Technovation, Elsevier, vol. 136(C).
    3. Schiefer, Tom & Mahr, Dominik & van Fenema, Paul C. & Mennens, Kars, 2024. "A collaborative approach to manage continuous service innovation," Technovation, Elsevier, vol. 134(C).
    4. Rossi, Luca & Pasca, Maria Giovina & Arcese, Gabriella & Poponi, Stefano, 2024. "Innovation, researcher and creativity: A complex indicator for territorial evaluation capacity," Technology in Society, Elsevier, vol. 77(C).

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