Cytology should create structured data sets without using synoptic reporting.

Area of Science:

• Medical Informatics
• Computational Pathology

Background:

• Cytology reports are crucial for cancer diagnosis but often exist as unstructured text.
• Extracting structured data from these reports is essential for large-scale analysis and research.

Discussion:

• Natural language processing (NLP) techniques can parse unstructured cytology reports to identify and extract key findings.
• Modifying laboratory information systems (LIS) can incorporate structured data fields directly into the reporting workflow.

Key Insights:

• Creation of structured datasets from cytology reports is achievable without synoptic reports.
• Both NLP and LIS modifications offer viable pathways for data structuring.

Outlook:

• This approach facilitates improved data aggregation for epidemiological studies and AI development.
• Standardizing data extraction methods enhances the utility of existing pathology archives.