Interactive Timeline Generator for Dynamic Medical Data Processing
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Solution Overview
Problem
Traditional data processing methods and graphical user interfaces are inadequate for analyzing and presenting large, complex datasets from diverse sources, leading to inefficient data analysis and ineffective conclusion-drawing, particularly in medical diagnostics where dispersed and disorganized medical records hinder timely and comprehensive patient health assessments.
Innovation Solution
A computerized system and method for dynamic data processing and graphical user interface generation, which includes a network interface to gather data from various sources, an input filter to identify structured and unstructured information, a data selector to analyze and prioritize data, and a timeline generator to create an interactive graphical user interface for presenting event timelines, facilitating better data analysis and presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional data processing methods are used to handle large datasets from diverse sources, then data can be stored and accessed, but the data cannot be analyzed uniformly and presented effectively in graphical user interfaces
Solution Approach 1:
The patent introduces an intermediary processing layer that includes data extraction modules, normalization modules, and relationship identification modules. This intermediary layer sits between the diverse data sources and the graphical user interface, translating various data formats into a unified structure that can be effectively analyzed and displayed, thereby resolving the contradiction between handling diverse data and maintaining system manageability
Solution Approach 2:
The system segments the complex data processing task into distinct functional modules: data extraction, normalization, relationship identification, and graphical presentation. Each module handles a specific aspect of the processing pipeline, allowing the system to manage complexity through modular design while maintaining the ability to process diverse data types uniformly
2Loss of information
If manual intervention is used to categorize and expand data points, then data can be organized into categories, but the process is time consuming and requires large amounts of manual effort
Solution Approach 1:
The system implements self-service through automated relationship identification algorithms that automatically analyze data points, identify their relationships, and categorize them without human intervention. The normalization module automatically standardizes data formats, and the relationship identification module autonomously determines connections between data elements, enabling the system to categorize and expand data points independently and efficiently
Solution Approach 2:
The patent replaces manual mechanical categorization processes with automated computational systems. Instead of human operators manually sorting and categorizing data points, the system uses algorithmic processes including pattern recognition, data mining, and automated classification algorithms to perform the same function at scale and speed, substituting mechanical human labor with automated computational mechanisms
3Adaptability or versatility
If raw data files are kept in various non-uniform formats, then data diversity is preserved, but the data cannot be analyzed uniformly for presentation in graphical user interfaces
Solution Approach 1:
The system applies local quality by implementing format-specific processing rules tailored to each data type while maintaining overall uniformity in the analysis pipeline. The normalization module contains specialized handlers for different data formats (text, images, videos, structured data) that apply appropriate transformation rules to each local data context, allowing the system to preserve data diversity characteristics while enabling uniform analysis across all formats through context-appropriate processing
Data Source
AI summary
Systems and methods for dynamic data processing and graphical user interface generation are provided. A system may include a network interface configured to request and receive, via a computer network from one or more sources in remote locations, electronic record data associated with an individual; an input filter configured to identify structured and unstructured information in the electronic record data; a data selector configured to analyze the structured and unstructured information; a timeline generator configured to generate, based on the analysis, interface information for displaying an interactive graphical user interface configured to present an event timeline of events in the electronic record data; and a display configured to provide the interactive graphical user interface based on the generated interface information.