20240028953. APPARATUS AND METHODS FOR ANALYZING DEFICIENCIES simplified abstract (Gravystack, Inc.)

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APPARATUS AND METHODS FOR ANALYZING DEFICIENCIES

Organization Name

Gravystack, Inc.

Inventor(s)

Chad Willardson of Phoenix AZ (US)

Scott Donnell of Phoenix AZ (US)

Travis Adams of Phoenix AZ (US)

APPARATUS AND METHODS FOR ANALYZING DEFICIENCIES - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240028953 titled 'APPARATUS AND METHODS FOR ANALYZING DEFICIENCIES

Simplified Explanation

The patent application describes an apparatus and method for analyzing deficiencies using machine learning models. Here is a simplified explanation of the abstract:

  • The apparatus includes a processor and memory.
  • The processor is configured to receive a behavioral data set that contains behavioral patterns.
  • The behavioral data set is used in machine learning models to determine deficiencies and/or objectives.

Potential Applications:

  • This technology can be applied in various industries where analyzing deficiencies is important, such as healthcare, finance, and manufacturing.
  • It can be used to identify deficiencies in patient behavior for personalized healthcare interventions.
  • In finance, it can help detect fraudulent behavior or identify patterns that lead to financial losses.
  • In manufacturing, it can be used to analyze behavioral patterns of machines to identify potential faults or inefficiencies.

Problems Solved:

  • This technology solves the problem of manually analyzing large amounts of behavioral data to identify deficiencies or objectives.
  • It automates the process using machine learning models, saving time and resources.
  • It can identify deficiencies or patterns that may not be easily detectable by human analysts.

Benefits:

  • The use of machine learning models allows for more accurate and efficient analysis of behavioral data.
  • It can provide real-time insights into deficiencies or objectives, enabling timely interventions or improvements.
  • The automation of the analysis process reduces the risk of human error and increases productivity.
  • It can help organizations optimize their operations by identifying areas of improvement based on behavioral patterns.


Original Abstract Submitted

an apparatus and method for analyzing deficiencies is disclosed. the apparatus includes processor and a memory configuring the processor to receive a behavioral data set that includes behavioral patterns. the behavioral data set is used in machine-learning models to determine a deficiency and/or an objective.

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