Temporal Objects for NLP Patient Health Timeline
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional natural language processing techniques lack the ability to determine temporal relationships between concepts, which is crucial for comprehensive data analytics and predictive modeling in healthcare, leading to incomplete understanding of patient health situations.
Innovation Solution
The development of temporal objects and a temporal domain that incorporate temporality into natural language processing, allowing for the extraction and analysis of temporal relationships between extracted terms, enabling the creation of robust patient profiles and health timelines.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional NLP techniques are used to extract terms from text, then term extraction is achieved, but temporal relationships between concepts cannot be determined
Solution Approach 1:
The patent segments the NLP process into distinct components: traditional term extraction is separated from temporal relationship analysis. Temporal objects are introduced as independent entities that capture temporal information (time expressions, duration, frequency, sequence) separately from concept extraction, allowing each component to be optimized independently while working together to provide comprehensive temporal understanding.
Solution Approach 2:
The patent introduces temporal objects as intermediary entities between traditional NLP term extraction and temporal relationship analysis. These temporal objects serve as mediators that bridge the gap by capturing temporal expressions and their relationships to concepts, enabling the system to determine temporal relationships without requiring a complete redesign of existing NLP techniques.
2Loss of information
If temporal objects and temporal domain are incorporated into NLP, then temporal relationships between concepts can be determined, but system complexity increases
Solution Approach 1:
The patent creates a universal temporal object framework that can handle multiple types of temporal relationships (time expressions, duration, frequency, sequence) through a unified structure. This multi-functional approach allows the system to capture various temporal aspects using consistent methods, reducing the need for separate specialized components for each temporal relationship type.
Solution Approach 2:
The patent implements a nested structure where temporal objects are embedded within the existing NLP framework. Temporal objects contain nested elements such as time expressions, concepts, and relationships, allowing temporal information to be integrated at multiple levels of the processing hierarchy without requiring a complete system restructuring.
3Loss of information
If temporal relationships are analyzed in addition to term extraction, then comprehensive understanding of patient health situations is achieved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by identifying and extracting temporal expressions and concepts during the initial term extraction phase, before full temporal relationship analysis is performed. This early identification allows the system to prepare temporal objects in advance, reducing the computational burden during subsequent temporal relationship determination and overall processing.
Solution Approach 2:
The patent implements partial action by allowing the system to perform temporal relationship analysis to the extent necessary for each specific application. The temporal object framework enables selective analysis where only relevant temporal relationships are fully processed, while less critical relationships can be handled with simpler methods, balancing completeness with processing efficiency.
Data Source
AI summary
Systems and methods for using temporal objects for natural language processing. One system includes an electronic processor configured to receive a set of electronic records of a patient, where each electronic record is associated with an event of the patent. The electronic processor is also configured to determine a temporal statement and an associated element, where the temporal statement and the associated element are associated with the event. The electronic processor is also configured to determine a temporal characteristic for the event based on the temporal statement and the associated element. The electronic processor is also configured to generate, based on the temporal characteristic, a temporal event entry associated with the event for a profile of the patient and enable access to the temporal event entry.