Adaptive Systems for Diverse Industry Applications
Legal Citation
Summary of the Inventive Concept
The present inventive concept expands the core technology of the original patent to novel applications beyond neuropsychiatric diseases, demonstrating its versatility and broad applicability across various industries.
Background and Problem Solved
The original patent's system and methods for screening, diagnosing, and stratifying patients were limited to neuropsychiatric diseases. However, the inventive concept addresses the problem of applying this technology to entirely different fields, such as agriculture, renewable energy, environmental monitoring, transportation, and equipment maintenance.
Detailed Description of the Inventive Concept
The new inventive concept leverages the Bayesian Decision List and machine executable code to analyze diverse input features and predict outcomes in various industries. For instance, the system can evaluate environmental factors to predict crop yields, optimize renewable energy output based on weather patterns, monitor water quality by analyzing sensor data, identify optimal transportation routes by evaluating traffic patterns, and predict equipment failures by analyzing sensor readings. These applications showcase the technology's adaptability and potential for significant impact across multiple sectors.
Novelty and Inventive Step
The new claims introduce novel applications of the original patent's core technology, demonstrating an inventive step beyond the original patent's scope. The inventive concept's ability to be applied to diverse industries, leveraging the same fundamental principles, constitutes a significant advancement.
Alternative Embodiments and Variations
Alternative embodiments of the inventive concept could include integrating additional data sources, such as IoT devices, social media, or weather services, to further enhance the accuracy and scope of predictions. Variations of the system could also be designed for real-time monitoring, enabling more rapid response to changing conditions.
Potential Commercial Applications and Market
The inventive concept has far-reaching commercial potential, with applications in agriculture, renewable energy, environmental monitoring, transportation, and equipment maintenance. The technology's adaptability and versatility make it an attractive solution for industries seeking to leverage data-driven insights and predictive analytics to drive decision-making and improve outcomes.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Machine learning, predictive analytics, and computational systems for data-driven decision making across multiple technical domains including healthcare, agriculture, energy, environmental monitoring, and industrial diagnostics
Person of Ordinary Skill (PHOSITA) Profile
A skilled practitioner with expertise in machine learning algorithms, statistical modeling, sensor data analysis, and interdisciplinary application of computational decision support systems, holding advanced degrees in computer science, data science, or related engineering disciplines
Obviousness Rationale
The source patent's core technology of using Bayesian Decision Lists and machine executable code for analyzing input features and predicting outcomes provides a fundamental framework that can be readily adapted to diverse technical domains. A PHOSITA would recognize the underlying computational methodology as universally applicable across different problem spaces, with the core algorithmic approach remaining consistent while input features and specific domain contexts change. The systematic approach of processing multiple input features through a probabilistic decision framework represents a generalizable technique that can be straightforwardly translated between different technical applications.
Obvious Combinations & Variations
Original Patent Information
| Patent Number | US 11,857,322 |
|---|---|
| Title | Systems and methods for screening, diagnosing, and stratifying patients |
| Assignee(s) | Neumora Therapeutics, Inc. |