Data Aggregation Interface for Critical Anomaly Prioritization
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Solution Overview
Problem
The overwhelming amount of information in medical and other fields leads to human professionals missing critical data anomalies due to information overload, with current systems failing to effectively prioritize and display critical information, leading to potential dangers and inefficiencies.
Innovation Solution
A computer-enabled system that aggregates data and visually displays critical anomalies separately from non-critical data on a circular interface, allowing users to quickly identify deviations from a norm and providing recommended interventions, with customizable parameters and intuitive navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all available data is displayed to professionals, then information completeness is improved, but human capacity to absorb and contextualize information is exceeded leading to missed critical data
Solution Approach 1:
The patent segments data by priority levels (critical, important, background) and displays them in hierarchical sections. Critical data appears in prominent positions with visual indicators, while less critical data is organized in separate sections that can be accessed as needed. This segmentation allows professionals to focus on critical information first without missing important context.
Solution Approach 2:
The patent extracts and highlights critical data elements from the overall data set, separating them from non-critical information. Critical results are pulled out and displayed with special visual indicators (such as color coding, icons, or positioning), allowing professionals to immediately identify and address the most important information without being overwhelmed by the complete data set.
2Device complexity
If data is distributed across multiple screens, then data organization is improved, but review time and complexity increase
Solution Approach 1:
The patent merges multiple data views into a single integrated display screen. Instead of requiring professionals to navigate between multiple screens or windows, the system consolidates critical data, important data, and background information into one comprehensive view with clear hierarchical organization. This allows complete data review in a single screen without increasing complexity.
3Loss of information
If reports are presented as text, then language-based information is preserved, but automated identification of critical results is difficult
Solution Approach 1:
The patent applies color coding and visual indicators to text-based reports to automatically highlight critical results. Critical findings are displayed with distinct visual markers (such as red highlighting, bold formatting, or special icons), while non-critical information uses different visual styles. This allows automated systems to easily identify and prioritize critical results while preserving the full text-based information for professional review.
Data Source
AI summary
Computer-enabled systems and methods aggregate data related to a particular subject or field and present the data in a simplified display. The data is divided into predetermined categories, which are graphically displayed in a predetermined arrangement. Systems and methods differentiate and visually display critical data abnormalities separately from non-critical data. The systems and methods enable an observer to identify the critical deviations or anomalies of data with respect to a predetermined base line by an intuitive visual display of all of the data from any sized data universe on a single screen. The data is indexed at multiple display levels such as a stack of one patient's data, a stack of all patient data for the universe of patients of a single practitioner, or a group of practitioners of any size. A portion of the display preferably may be selected and expanded to show only that portion in greater detail.