Clinical Natural Language Processing (NLP) systems require a semantic schema comprised of domain-specific concepts and associated modifiers to accurately extract information. NLP systems leverage this schema to extract meaning from texts. In the clinical domain, creating a schema requires input from clinicians and NLP experts.

The proposed technology bridges the gap between clinicians and the development of NLP systems by seamlessly analyzing data extracted from handwritten clinical notes to provide healthcare professionals with information that supports better decision making. A web-based software tool supports users in developing domain content. Content is integrated into a system that processes the handwritten clinical notes and subsequently provides actionable data to doctors and clinicians. The notes can be reviewed and corrected for accuracy. Additionally, users can search for specific annotations based on semantic content.