Symbol delimited and defined data blocks to write rich data stories for use with artificial intelligence

EP4445380A4Pending Publication Date: 2025-11-26MOFAIP LLC
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Patent Information

Application Number
EP2022937332
Authority / Receiving Office
EP · EP
Patent Type
Applications
Current Assignee / Owner
Priority Date
2022-01-28
Filing Date
2022-12-12
Publication Date
2025-11-26

AI Technical Summary

Technical Problem

Current medical documentation systems and Electronic Health Records (EHRs) lack interoperability and uniformity, leading to fragmentation of health data, with complex standards that require medical knowledge and are not easily applied, especially across different countries and languages, making it challenging to analyze and link patient demographics, diagnoses, and treatments.

Method used

The use of symbol-delimited and symbol-defined data blocks, linked to standardized symbols like emojis or Unicode characters, allows for order-agnostic and structureless data collation, enabling automatic categorization and analysis by AI, and supports language-agnostic, database-agnostic, and platform-agnostic data storage and retrieval, facilitating seamless integration and research across diverse systems.

Benefits of technology

This approach simplifies data retrieval and analysis, reduces manual effort, and enhances research capabilities by automatically de-identifying and aggregating health data, allowing for targeted data retrieval and creation of automatic datasets for epidemiology research, while addressing privacy concerns through customizable and encryptable anatomic site encoding.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present invention includes a method for data collation, retrieval, organization, analysis, and summarization of health data by utilizing order-agnostic symbol delimited and symbol defined data linked to standardized symbols, such as emojis or unicode characters. A file name and metadata building method uses a data block engine with low-character-count, symbolic delimiters and symbolic definitions automatically applied to each data field. The data-blocks are orderless and structureless, with no header requirements. Similar to physical construction blocks, the digital data blocks can be constructed, built upon, deconstructed, rearranged, or modified. The data blocks build digital foundations on which artificial intelligence and / or machine learning can gather, collate, modify, and serve language agnostic, database agnostic, and platform agnostic data for individual patients or for populations, such as in a research search engine that retrieves automatically de-identified datasets of data tagged as "OK" to use in research among other tags, solving privacy concerns at the same time.
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Citation Information

Patent Citations

  • Automated dicom pre-fetch application

    US20100010983A1