Applying Bayesian Decision Lists to Diverse Industries
Legal Citation
Summary of the Inventive Concept
This inventive concept leverages the core technology of Bayesian Decision Lists to develop novel applications in various industries, including agriculture, supply chain logistics, marketing, energy consumption, and manufacturing.
Background and Problem Solved
The original patent disclosed systems and methods for screening, diagnosing, and stratifying patients relating to neuropsychiatric diseases. However, the potential of Bayesian Decision Lists extends far beyond healthcare. This inventive concept addresses the limitation of the original patent by applying the core technology to entirely new industries, solving complex problems in these fields.
Detailed Description of the Inventive Concept
The new inventive concept involves the development of systems and methods that utilize Bayesian Decision Lists to tackle challenges in diverse industries. For instance, in agriculture, the system can predict crop yields based on historical climate data and crop yield information. In supply chain logistics, the Bayesian Decision List can optimize logistics by identifying factors affecting efficiency. Similarly, in marketing, the system can evaluate the effectiveness of marketing campaigns by analyzing consumer response data. In energy consumption, the system can predict energy consumption patterns based on historical data and environmental factors. Finally, in manufacturing, the Bayesian Decision List can optimize resource allocation by identifying factors affecting manufacturing efficiency.
Novelty and Inventive Step
The new claims introduce novel applications of Bayesian Decision Lists in industries unrelated to healthcare, which were not considered in the original patent. The inventive step lies in the adaptation of the core technology to address specific challenges in these new industries, resulting in innovative solutions with significant commercial potential.
Alternative Embodiments and Variations
Alternative embodiments of this inventive concept could include the integration of additional data sources, such as IoT sensors or social media data, to enhance the predictive capabilities of the Bayesian Decision Lists. Variations could also involve the development of specialized Bayesian Decision Lists tailored to specific industries or use cases.
Potential Commercial Applications and Market
The commercial potential of this inventive concept is substantial, with potential applications in multiple industries. The target market includes companies operating in agriculture, supply chain logistics, marketing, energy consumption, and manufacturing, as well as startups and research institutions seeking to leverage AI and machine learning for innovation.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Machine learning, predictive analytics, and computational decision support systems with expertise in Bayesian modeling, data processing, and multi-domain predictive modeling techniques
Person of Ordinary Skill (PHOSITA) Profile
A skilled practitioner with advanced degrees in computer science, statistics, or engineering, proficient in machine learning algorithms, data analysis, and computational modeling across multiple technical domains
Obviousness Rationale
The PTD demonstrates that the core Bayesian Decision List methodology from the source patent can be readily adapted to diverse industrial contexts by applying the same fundamental machine learning principles. A PHOSITA would recognize that the underlying computational approach of processing input features through probabilistic decision trees remains consistent across domains. The technical transfer involves substituting domain-specific input features while maintaining the core algorithmic structure, which represents a predictable engineering adaptation.
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. |