Medical Data Timeline Interface with Sliding Window Analysis
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Solution Overview
Problem
Current medical information systems face challenges in effectively displaying and analyzing vast amounts of data over time, making it difficult for medical practitioners to accurately diagnose and treat patients, as individual normal ranges can vary significantly, and existing visualization methods do not adequately account for symptomatic and asymptomatic biological subsystems.
Innovation Solution
A computer-implemented method and system that generates a timeline with adjustable sliding windows to highlight specific data points, including icons for life forms, biological samples, measurements, and treatments, allowing for improved data visualization and analysis by displaying biomarkers and other measurements in information plots, with features like interpolation and user-adjustable zooming.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If vast amounts of medical data are captured and stored over time, then the quantity of information available for diagnosis increases, but the complexity of processing and visualizing this data becomes unmanageable for single practitioners
Solution Approach 1:
The patent introduces an AI-based intermediary system that automatically processes, analyzes, and synthesizes vast amounts of medical data. This intermediary handles the complex computational tasks of pattern recognition, anomaly detection, and data synthesis, allowing practitioners to access insights without directly managing the underlying data complexity.
Solution Approach 2:
The patent replaces manual data processing and visual analysis with automated AI algorithms and machine learning models. These computational systems automatically detect patterns, correlate findings across multiple data sources, and generate visual representations, substituting the mechanical cognitive effort previously required from practitioners.
2Ease of operation
If traditional visualization methods are used to display medical data, then the simplicity of display is maintained, but the ability to detect anomalies and recognize individual normal ranges is insufficient
Solution Approach 1:
The patent applies local quality by customizing visualizations to highlight specific anomalies, deviations from individual baselines, or clinically relevant patterns in different regions of the data display. Rather than uniform presentation, the system adapts the visual emphasis to local data characteristics and clinical questions.
Solution Approach 2:
The patent transforms data from traditional two-dimensional tables or graphs into multi-dimensional visual representations that incorporate temporal trends, comparative benchmarks, and anomaly probabilities simultaneously. This additional dimensional information helps practitioners detect patterns and anomalies that would be invisible in conventional displays.
3Device complexity
If individual normal ranges and asymptomatic samples are not accounted for, then the simplicity of establishing reference ranges is maintained, but the accuracy of diagnosis and treatment monitoring deteriorates
Solution Approach 1:
The patent performs preliminary analysis by automatically establishing individual baseline ranges and identifying asymptomatic patterns before clinical decisions are made. The system pre-processes historical data to create personalized reference ranges, so that when practitioners review current data, individual baselines are already established and ready for comparison.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously learns from new data points, adjusting individual baseline ranges over time as more information becomes available. This feedback loop refines the precision of personalized reference ranges, allowing the system to adapt to individual variations in normal physiology.
Data Source
AI summary
A user interface for medical information includes a timeline that can be highlighted or selected by a time window with a time duration, and the information plots of biomarkers displayed in subsystem displays can update to display the biomarker information for the time duration highlighted by the time window. The trendline, baseline, and data points shown on the information plot(s) can also be adjusted to display only information during the time duration highlighted or selected by the time window.