AI-Supported Digital Microscopy Diagnostics in Primary Health Care Laboratories: Scoping Review.

Area of Science:

• Medical Diagnostics
• Health Informatics
• Biotechnology

Background:

• Digital microscopy with AI is expanding in healthcare, primarily in advanced labs.
• AI-enhanced microscopy offers significant potential for primary care by improving diagnostic access through automation and reducing the need for on-site experts.
• This is the first scoping review to examine AI-supported digital microscopy in primary health care laboratories.

Purpose of the Study:

• To map published peer-reviewed studies on AI-supported digital microscopy in primary health care laboratories.
• To provide an overview of the current research landscape and identify implementation challenges.

Main Methods:

• Systematic search of PubMed, Web of Science, Embase, and IEEE databases.
• Inclusion criteria: digital microscopy, AI, comparison to standard diagnostics, primary health care setting, peer-reviewed, English language, human samples, sample-level diagnosis.
• Methodology followed the Joanna Briggs Institute guidelines for scoping reviews, with dual researcher selection and consensus for disagreements.

Main Results:

• 22 studies were included from 3403 screened papers.
• Analyzed samples included blood, urine, cytology, stool, and sputum for various conditions.
• AI-supported digital microscopy demonstrated comparable diagnostic accuracy and higher sensitivity than manual microscopy in most studies.

Conclusions:

• AI-supported digital microscopy achieves comparable diagnostic accuracy for multiple targets in primary health care.
• The technology shows potential for improved diagnostic sensitivity, especially in resource-limited settings.
• Further research on scalability and cost-effectiveness is needed to enhance diagnostic accessibility.