To evaluate the current capabilities and readiness of AI tools in clinical pathology, particularly in image-based diagnostics.
Key Findings:
AI significantly reduces review time in clinical microbiology by screening negative slides.
AI is viewed as augmented intelligence, supporting rather than replacing human expertise.
Integration into existing workflows is crucial for clinical adoption of AI tools.
Interpretation:
AI tools are not yet fully autonomous but can enhance diagnostic efficiency and quality in pathology, especially under workforce constraints.
Limitations:
Current AI tools may not be fully validated for diverse real-world conditions.
Pathologists face challenges in defining ground truth due to evolving AI capabilities.
Conclusion:
AI has the potential to transform pathology by improving efficiency and diagnostic accuracy, but careful evaluation and integration are essential for clinical readiness.
