Platelet Cell Data Processing System for Diagnostic Categorization
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Solution Overview
Problem
Platelet cell data from blood samples, as analyzed by hematology analyzers, is not in a form that is readily useful for medical diagnostics and research due to its raw format.
Innovation Solution
A system and method that processes platelet cell data by establishing threshold ranges and categorizing it based on user-defined parameters, allowing for the computation and display of platelet cell counts and percentages in tabular and graphical forms, such as cytograms and histograms, to facilitate medical diagnostics and research.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If platelet cell data is stored in raw format with individual cell parameters, then the data retains complete measurement information, but the data is not readily useful for medical diagnostic and research purposes
Solution Approach 1:
The patent segments the continuous platelet cell data into discrete categories based on volume and refractive index ranges. Individual platelet cells are classified into categorical groups (e.g., small/normal/large volume, low/normal/high refractive index), transforming raw continuous measurements into structured categorical data that is more useful for clinical interpretation while preserving the essential characteristics of the original measurements.
Solution Approach 2:
The patent transforms the data from raw continuous parameters (individual cell volume and refractive index values) into processed categorical parameters (classified ranges and computed percentages). This parameter transformation converts unusable raw data into clinically meaningful information through systematic classification and computation of distribution statistics.
2Ease of operation
If platelet cell data is categorized into multiple ranges and categories, then the data becomes useful for diagnostics, but additional processing steps are required
Solution Approach 1:
The patent performs preliminary classification of platelet cells into volume and refractive index categories during the data processing phase. By pre-establishing the categorization framework and automatically assigning each cell to appropriate categories, the system prepares the data in advance for clinical interpretation, eliminating the need for manual analysis and improving overall diagnostic workflow efficiency.
Solution Approach 2:
The system automatically computes the distribution statistics and percentages for each category without requiring manual intervention. The processor independently performs the classification, counting, and percentage calculation, making the data ready for immediate clinical use while maintaining high processing efficiency through automated self-service operations.
Data Source
AI summary
Platelet cell data may be obtained from analysis of a blood sample by a hematology analyzer or like device. Systems and apparatus may process the platelet cell data in accordance with platelet parameter thresholds selected by a user. The platelet cell data may then be categorized and displayed in one or more useful forms for medical diagnostic and/or research purposes. The platelet cell data may be categorized and displayed in, e.g., tabular and/or graphical form based on the user-selected platelet parameter thresholds. Methods of processing platelet cell data for categorizing and displaying the platelet cell data in one or more useful forms are also provided, as are other aspects.