Treatment Plan Data Transformation for Consistent Oncology Templates

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Solution Overview

Problem

The manual process of creating oncology treatment plans involves tedious data extraction and navigation through large quantities of unstructured data, leading to errors and inefficiencies.

Innovation Solution

A computer-implemented method that queries data sources for treatment plan templates, parses raw data using complex regular expressions and standard keywords, constructs formatted data in JSON format, and generates structured data with hierarchical organization, allowing for real-time updates and error identification.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual navigation through large quantities of unstructured data is used to extract treatment plan information, then data extraction can be performed, but the process becomes tedious and error-prone

Engineering Contradiction:

Improvedata extraction accuracyVSAvoidmanual data navigation difficulty

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent replaces manual mechanical navigation through data with automated computer-based processing. The system uses software to automatically query data sources, parse raw data, extract elements using regular expressions and keywords, and construct formatted data, eliminating the need for analysts to manually navigate through unstructured data and reducing both time consumption and error rates

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service by allowing the automated processing pipeline to handle data extraction and transformation independently. The computer-implemented method autonomously queries data sources, processes raw data through parsing and extraction, constructs formatted data in JSON format, and generates structured data with hierarchical organization without requiring continuous manual intervention

Inventive Principle:

Principle #25Self-service

2Adaptability or versatility

If multiple data formats (XML, HTML, PDF) are supported from different data sources, then data accessibility is improved, but data consistency and processing complexity increase

Engineering Contradiction:

Improvedata format compatibilityVSAvoiddata processing system complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces an intermediary processing layer that standardizes data from multiple formats. The system uses a unified parsing approach with regular expressions and standard keywords that can handle XML, HTML, and PDF formats through a common processing pipeline, transforming diverse input formats into a consistent JSON structure without requiring separate processing logic for each format

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The system implements universal processing capabilities that handle multiple data formats through a single integrated method. The computer-implemented method uses format-agnostic parsing techniques and standard extraction rules that work across XML, HTML, and PDF sources, enabling one processing system to serve multiple data source types without increasing complexity

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Productivity

If automated data extraction using regular expressions and keywords is implemented, then productivity increases, but precision in extracting relevant elements may decrease

Engineering Contradiction:

Improvedata extraction speedVSAvoiddata extraction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system incorporates feedback mechanisms where extracted elements are validated against expected patterns and structures. The parsing process uses regular expressions and standard keywords with defined schemas that provide feedback on extraction success, allowing the system to verify that extracted data meets precision requirements while maintaining automated high-speed processing

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent adjusts extraction parameters such as regular expression patterns and keyword lists based on data characteristics. The system can modify extraction sensitivity and specificity parameters to optimize the balance between processing speed and extraction accuracy for different data sources and formats

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS12620467B2Data extraction and data-structure transformation for improving data accessibility and usage consistency

Publication Date: 2026.05.05 CERNER INNOVATION INC

AI summary

A system and computer-implemented method includes querying a data source for treatment plan templates based on a medical condition of a patient. Raw data related to treatment plan templates is received from the data source. The raw data includes text information. Raw data is parsed, and tags are identified. elements are extracted from the tags using complex regular expression and keywords. Formatted data is constructed from the elements in a machine-readable format. The elements are arranged in a hierarchical structure within the formatted data. Structured data having data frames is generated based on the formatted data. The structured data is provided to a medical provider for review. An update in the structured data is received from the medical provider based on a deviation in schedule provided in the treatment plan templates. The treatment plans are generated based on incorporation of the update into the structured data.