AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Protocol for a Scoping Review

Area of Science:

• Medical Informatics
• Digital Pathology
• Artificial Intelligence in Healthcare

Background:

• Digital microscopy with AI is expanding in healthcare, primarily in advanced labs.
• AI-enhanced microscopy offers significant potential for primary care by automating diagnostics and reducing reliance on on-site specialists.
• This review addresses the gap in understanding AI-supported digital microscopy applications within primary health care laboratories.

Purpose of the Study:

• To conduct a scoping review of peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories.
• To map the existing research landscape and provide an overview of current applications and findings.

Main Methods:

• Systematic search of major databases (PubMed, Web of Science, Embase, IEEE) for English-language, peer-reviewed articles.
• Inclusion criteria: AI-supported digital microscopy for diagnosis in primary health care settings (no on-site pathologist, simple sample preparation).
• Data extraction and analysis by two independent researchers, adhering to JBI methodology for scoping reviews.

Main Results:

• The review protocol was published in January 2024, with completion in March 2024.
• Systematic searches are pending peer review of the protocol.
• The full scoping review is projected for completion by the end of 2024.

Conclusions:

• The anticipated systematic review will identify diseases benefiting from AI-digital microscopy in primary care.
• It will highlight common challenges and successful strategies for implementing these technologies in primary health care laboratories.
• Findings will guide future research and development for AI-driven diagnostics in underserved healthcare settings.