Implant Plan Evaluation Model Training for Expert Preference Alignment

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Solution Overview

Problem

Existing surgical planning systems struggle to converge on a singular solution for implant placement and parameter selection due to varying clinical constraints and expert preferences, leading to considerable variation among surgeons in choosing implant options.

Innovation Solution

A machine learning-based implant plan evaluation model is trained using pairs of user-defined and automatically generated implant options, adjusting its scoring to favor expert preferences by comparing and updating weights for parameters, ensuring the model selects implant options most likely to be chosen by surgeons.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If multiple implant plan options are generated based on varying clinical constraints and expert preferences, then the system provides more comprehensive surgical planning options, but the system cannot converge on a singular solution leading to considerable variation among surgeons

Engineering Contradiction:

Improvecomprehensive surgical planning optionsVSAvoidconsistency of implant selection

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The system changes the parameters of implant plan options by adjusting weights assigned to different parameters (such as safety, surgical efficiency, and clinical constraints) to generate varied yet optimized implant plans that balance comprehensiveness with convergence toward optimal solutions

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system incorporates feedback loops where implant plan options are evaluated against clinical constraints and expert preferences, with results used to refine and adjust the planning process, enabling convergence while maintaining adaptability to different surgical scenarios

Inventive Principle:

Principle #23Feedback

2Reliability

If the model is trained to favor expert preferences by comparing user-defined and automatically generated implant options, then the model selects implant options most likely to be chosen by surgeons, but the model complexity increases

Engineering Contradiction:

Improveaccuracy of implant option selectionVSAvoidmodel training and evaluation complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs preliminary actions by pre-training the model with pairs of user-defined and automatically generated implant options before actual surgical planning, establishing expert preference patterns in advance to improve selection accuracy without increasing real-time complexity

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system creates copies of implant plan options (both user-defined and automatically generated) for comparative evaluation during training, allowing the model to learn from multiple variations while maintaining manageable complexity through structured comparison protocols

Inventive Principle:

Principle #26Copying

Data Source

PatentUS20250325379A1Systems and methods for training and using an implant plan evaluation model

Publication Date: 2025.10.23 MAZOR ROBOTICS

AI summary

Systems and methods for training an implant plan evaluation model is provided. A first implant plan option having a first set of parameters and a second implant plan option having a second set of parameters may be received. The first set of parameters and the second set of parameters may be inputted into a model configured to score the first implant plan option based on the first set of parameters and the second implant plan option based on the second set of parameters. The score of the first implant plan option and the score of the second implant plan option may be compared. when the score of the second implant plan option is higher than the score of the first implant plan option the model may be adjusted to score the first implant plan option higher than the second implant plan option.