Prospective real-world implementation of deep learning systems in healthcare: a systematic review guided by implementation science - Takeaways - MDSpire

Prospective real-world implementation of deep learning systems in healthcare: a systematic review guided by implementation science

  • By

  • Rachel Marjorie Wei Wen Tseng

  • Li Cheng Ong

  • Jocelyn Hui Lin Goh

  • Yibing Chen

  • Tina Chen

  • Elaine Lum

  • Yih-Chung Tham

  • January 23, 2026

  • 0 min

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  • 1

    Deep learning applications in healthcare are moving beyond proof-of-concept studies, but real-world implementation remains unclear.

  • 2

    This systematic review analyzed 20 studies, primarily in ophthalmology, assessing the effectiveness of deep learning in clinical workflows.

  • 3

    Adoption and appropriateness were the most evaluated outcomes, while implementation costs and sustainability were rarely addressed.

  • 4

    Stakeholder acceptability was evaluated in only 8 of the included studies, highlighting a gap in understanding user perspectives.

  • 5

    Continued research using hybrid effectiveness-implementation designs is essential for the successful adoption of deep learning in clinical practice.

Original Source(s)

Prospective real-world implementation of deep learning systems in healthcare: a systematic review guided by implementation science

  • by Rachel Marjorie Wei Wen Tseng, Li Cheng Ong, Jocelyn Hui Lin Goh, Yibing Chen, Tina Chen, Elaine Lum, Yih-Chung Tham

  • January 23, 2026

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