CASM Temporal-Interaction Scoring for Complex Adaptive Systems
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Solution Overview
Problem
Conventional mathematical and statistical methods are inadequate for quantifying the workings of complex adaptive systems, particularly in fields like drug development and medicine, where living systems exhibit complex adaptive behavior that is not adequately captured by traditional SI units of measurement.
Innovation Solution
The development of Complex Adaptive Systems Metrology (CASM) methods and systems that compute universally standardized, bi-directional temporal-interaction scores and benefit-and-harm scores from multivariate time series data, enabling the measurement of how individual complex adaptive systems function, respond to environments, and interact over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional mathematical and statistical methods are used to measure complex adaptive systems, then measurement can be performed with established tools, but the measurement precision and reliability are insufficient for capturing temporal interactions in living systems
Solution Approach 1:
The patent segments the measurement process into distinct computational modules: (1) data reception module receiving multivariate time-series data, (2) pre-processing module decomposing time series to distinguish temporal interactions from trends, (3) digitizing module converting continuous variables to digital format, and (4) computation module calculating temporal-interaction scores. This segmentation enables precise measurement of temporal interactions while managing system complexity through modular architecture.
Solution Approach 2:
The patent introduces a new computational dimension by calculating temporal-interaction scores that quantify the strength and direction of interactions between variables over time. This goes beyond traditional statistical measures by adding a temporal-dynamics dimension to the measurement space, enabling differentiation of causal relationships in complex adaptive systems.
2Adaptability or versatility
If conventional SI units of measurement are applied to living systems, then standardization is achieved, but the adaptability and effectiveness for personalized medicine are reduced
Solution Approach 1:
The patent transforms conventional measurement parameters by introducing temporal-interaction scores that capture dynamic relationships between variables. Instead of static measurements, the system computes time-dependent interaction strengths and directions, enabling personalized treatment strategies that adapt to individual temporal patterns in complex adaptive systems.
Solution Approach 2:
The patent introduces temporal-interaction scores as intermediary computational metrics that bridge conventional measurements and personalized treatment decisions. These scores serve as mediators that translate raw time-series data into actionable insights about system dynamics, preserving temporal-dynamics information while enabling clinical decision-making.
3Difficulty of detecting and measuring
If multivariate time-series data is analyzed without specialized processing, then data collection is simplified, but the difficulty of detecting and measuring temporal interactions increases
Solution Approach 1:
The patent applies preliminary processing actions to multivariate time-series data before analysis: (1) decomposition of time series to separate temporal interactions from linear and nonlinear trends, and (2) digitizing of continuous variables to discrete digital format. These preliminary actions reduce the difficulty of detecting temporal interactions by preprocessing the data into a more analyzable form.
Solution Approach 2:
The patent replaces traditional mechanical/statistical measurement approaches with computational methods. Instead of relying on conventional statistical tools, the system uses computational algorithms to calculate temporal-interaction scores, substituting computational processing for traditional measurement mechanics.
Data Source
AI summary
Methods and systems are described for a computer-implemented complex adaptive systems metrology (CASM) technique for generating universally and mathematically standardized scores that quantify longitudinal evidence for either temporal-interaction scores or temporal-interaction benefit-and-harm scores to determine a quantitative significance estimate of scores for either standardized temporal-interaction scores or the standardized temporal-interaction benefit-and-harm scores.