AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Scoping Review
AI-supported digital microscopy achieved comparable diagnostic accuracy to the reference standard for diagnosing multiple targets in primary health care laboratories and may be particularly advantageous for improving diagnostic sensitivity. With further research addressing challenges such as scalability and cost-effectiveness, AI-supported digital microscopy could improve access to diagnostics, especially in expert-scarce and resource-limited settings.
Authors
- Nina Linder (ORCID: https://orcid.org/0000-0003-3930-0513)
- Johan Lundin (ORCID: https://orcid.org/0000-0002-2681-4139)
- Joar von Bahr (ORCID: https://orcid.org/0009-0009-8687-2160)
- Antti Suutala (ORCID: https://orcid.org/0009-0004-7585-1624)
- Andreas Mårtensson (ORCID: https://orcid.org/0000-0001-7504-8365)
- Vinod Diwan (ORCID: https://orcid.org/0000-0002-5831-2037)
Institutions
- Uppsala University (SE)
- University of Helsinki (FI)
- Uppsala University Hospital (SE)
- Karolinska Institutet (SE)
- Institute for Molecular Medicine Finland (FI)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-11-17
- DOI
- https://doi.org/10.2196/78500
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00