Enhanced Systems and Methods for Mental Health Diagnosis and Treatment
Legal Citation
Summary of the Inventive Concept
An advanced system for evaluating, diagnosing, and stratifying patients with mental health issues, providing accurate probability scores, confidence levels, and personalized treatment plans.
Background and Problem Solved
The original patent disclosed systems and methods for screening, diagnosing, and stratifying patients with neuropsychiatric diseases. However, these systems lacked the ability to provide accurate probability scores, confidence levels, and personalized treatment plans. The present inventive concept addresses these limitations by introducing enhanced systems and methods that improve the accuracy and effectiveness of mental health diagnosis and treatment.
Detailed Description of the Inventive Concept
The new inventive concept comprises systems and methods that integrate advanced machine learning algorithms, Bayesian Decision Lists, and cognitive task outcome measures to provide accurate probability scores and confidence levels for mental health conditions. The systems can output mental health conditions with a probability score of accuracy, recommend personalized treatment plans based on the patient's medical history, identify potential biomarkers, and track the progress of a patient's mental health condition in real-time. The methods involve receiving input features from patients, applying Bayesian Decision Lists, and outputting mental health conditions with confidence levels.
Novelty and Inventive Step
The new claims introduce the concept of probability scores, confidence levels, and personalized treatment plans, which are not present in the original patent. The use of Bayesian Decision Lists and cognitive task outcome measures to improve the accuracy of mental health diagnosis is also novel and non-obvious.
Alternative Embodiments and Variations
Alternative embodiments of the inventive concept could include the use of different machine learning algorithms, additional input features, or integration with wearable devices and electronic health records. Variations could include systems for diagnosing specific mental health conditions, such as bi-polar disorder or PTSD.
Potential Commercial Applications and Market
The inventive concept has significant commercial potential in the mental health industry, with applications in healthcare providers, pharmaceutical companies, and research institutions. The market for mental health diagnosis and treatment is growing rapidly, and the present inventive concept is well-positioned to capture a significant share of this market.
Section 103 Obviousness Analysis (PHOSITA)
Field of Art
Mental health diagnostics, machine learning, and computational medical assessment systems, with expertise in probabilistic modeling, cognitive task analysis, and patient screening technologies
Person of Ordinary Skill (PHOSITA) Profile
A professional with advanced degrees in computer science, biomedical engineering, or clinical informatics, possessing expertise in machine learning algorithms, statistical modeling, and healthcare data processing techniques
Obviousness Rationale
A PHOSITA would recognize that extending the source patent's mental health diagnostic system with probability scoring, confidence levels, and personalized treatment recommendations represents a predictable enhancement using standard machine learning and statistical techniques. The core diagnostic framework remains consistent, with the PTD introducing incremental improvements in quantification and personalization of diagnostic outputs. These variations would be considered obvious improvements within the existing technological paradigm of computational medical diagnostics.
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. |