Requirement | Description | |
---|---|---|
R1 | Appropriate terminology | Use accepted terminologies and vocabularies whenever possible |
R2 | Cancer-specific content | Provide expressivity necessary to develop appropriately detailed descriptions of cancer treatment and progression |
R3 | Available tooling | Align with existing APIs, schemata, validators, etc. |
R4 | Community-driven modeling | Use community contributions and critiques to improve models |
R5 | Compatibility with existing NLP infrastructure | Facilitate interaction with existing NLP tools and type systems. |
R6 | Combinations of structured and unstructured data | Support the combination of structured data represented in EMRs with unstructured details extracted from clinical texts. |
R7 | Multi-level modeling | Support summarization of data across multiple levels of abstraction, ranging from instances/mentions to documents, episodes (collections of records indicating a distinct phase in disease progression such as diagnosis or treatment), and high-level summaries of cancers and tumors. |
R8 | Provenance | Preserve and expose linkages between abstracted models and source data |