Medical NLP System

Medical NLP System is a system that analyzes clinical documents in free text format (doctor's notes, discharge summaries, radiology reports) using natural language processing (NLP) to convert them into structured information and insights.

The system supports coding, searching, and analytical processes by extracting entities such as diagnosis, medication, and findings from texts.

Other names / abbreviations: Clinical NLP, Natural Language Processing.

What is it used for?

The medical NLP system makes hidden information in free text accessible; it enables the production of structured data for coding, quality measurement, and analytics.

Key features

• Entity extraction: Extracting diagnosis, medication, and findings from text.
• Coding support: Assisting with diagnosis/procedure coding.
• Search and analytics: Making free text searchable/analyzable.
• Turkish language support: Processing clinical Turkish texts (in supporting solutions).

Integration and standards

The Medical NLP System does not operate in isolation; it typically exchanges data with the following systems and processes:

• EMR / HBYS
• Discharge summary summarization system
• Analytics/data warehouse

Frequently referenced standards and regulations:

• FHIR
• SNOMED CT / ICD
• KVKK

Benefits provided

• Data extraction from free text
• Coding and quality support
• Structuring for analytics

Selection and evaluation criteria

The main criteria considered when evaluating a medical NLP system include:

• Support for Turkish clinical language
• Accuracy and validation
• Integration

Points to consider

• Extraction accuracy must be validated in a clinical context.
• Privacy (KVKK) is of particular importance in text data.