18059082. VARIABLE CONFIDENCE MACHINE LEARNING simplified abstract (GE Precision Healthcare LLC)
Contents
- 1 VARIABLE CONFIDENCE MACHINE LEARNING
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 VARIABLE CONFIDENCE MACHINE LEARNING - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
VARIABLE CONFIDENCE MACHINE LEARNING
Organization Name
Inventor(s)
Rahul Venkataramani of Bengaluru (IN)
Vikram Reddy Melapudi of Bangalore (IN)
VARIABLE CONFIDENCE MACHINE LEARNING - A simplified explanation of the abstract
This abstract first appeared for US patent application 18059082 titled 'VARIABLE CONFIDENCE MACHINE LEARNING
Simplified Explanation
The abstract of the patent application describes a system that utilizes machine learning to perform regression tasks on medical images, taking into account a user-specified confidence indicator.
- This system allows for variable confidence machine learning.
- The machine learning model receives both the medical image and a user-specified confidence indicator as input.
- The system can access and analyze medical images to provide valuable insights.
Potential Applications
This technology could be applied in various fields such as healthcare, diagnostics, and image analysis.
Problems Solved
This technology helps in improving the accuracy and reliability of machine learning models when analyzing medical images.
Benefits
The system provides a more comprehensive analysis of medical images by incorporating user-specified confidence indicators. It can assist healthcare professionals in making more informed decisions based on the analysis of medical images.
Potential Commercial Applications
- Healthcare industry for diagnostics and treatment planning
- Medical imaging companies for developing advanced analysis tools
Possible Prior Art
There may be existing systems that use machine learning for medical image analysis, but the incorporation of user-specified confidence indicators could be a novel aspect of this technology.
Unanswered Questions
The article does not address the specific measures taken to ensure the privacy and security of the medical image data used in the system.
What are the computational requirements for executing the machine learning model on medical images?
The article does not provide information on the computational resources needed to run the machine learning model on medical images.
Original Abstract Submitted
Systems/techniques that facilitate variable confidence machine learning are provided. In various embodiments, a system can access a medical image. In various aspects, the system can perform, via execution of a machine learning model, a regression task on the medical image, wherein the machine learning model can receive as input both the medical image and a user-specified confidence indicator.
