A method and system for evaluating microscopic endoscopic procedures

By preprocessing the microendoscopic operation data stream and performing causal analysis using Bayesian structural equation modeling, combined with a dynamic and efficient operation library, the problem of lacking strategy logic modeling in traditional evaluation methods is solved, enabling objective and impartial evaluation of microendoscopic operations and accurate operational improvement suggestions.

CN122022193BActive Publication Date: 2026-07-03AFFILIATED HUSN HOSPITAL OF FUDAN UNIV
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Patent Information

Application Number
CN202610467021.7
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2026-04-10
Publication Date
2026-07-03
Estimated Expiration
2046-04-10

AI Technical Summary

Technical Problem

Traditional methods for assessing microendoscopic techniques lack modeling of the strategic logic in the operator's behavior, resulting in insufficient accuracy and an inability to effectively quantify operational skills.

Method used

By preprocessing the microendoscopic operation data stream, the original motion primitive sequence and equipment event sequence are extracted. Causal analysis is performed using a Bayesian structural equation model to generate a comprehensive operation evaluation result. Counterfactual attribution is performed using a dynamic and efficient operation library to quantify the operator's strategy effectiveness and robustness.

Benefits of technology

It enables objective and impartial evaluation of microendoscopic procedures, quantifies the operator's intrinsic effectiveness and strategy robustness, and improves the accuracy of evaluation and the pertinence of operational improvement suggestions.

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Abstract

This invention provides a method and system for evaluating microendoscopic operations, comprising: preprocessing and extracting features from a microendoscopic operation data stream to generate a raw motion primitive sequence and a device event sequence; obtaining a comprehensive objective performance score within an operation analysis window based on preset microendoscopic operation meta-indicators; simultaneously generating a conditional Pareto front for each anatomical site by combining a dynamic high-efficiency operation library; acquiring environmental state data; analyzing the operation to be evaluated using a preset strategy performance evaluation mechanism to obtain strategy performance evaluation results; performing causal analysis on the operation to be evaluated based on a Bayesian structural equation model and counterfactual attribution using the dynamic high-efficiency operation library to generate a causal analysis dataset; and performing a comprehensive operation evaluation based on the comprehensive objective performance score, the conditional Pareto front, the strategy performance evaluation results, and the causal analysis dataset to generate a comprehensive operation evaluation result, thereby improving the accuracy of microendoscopic operation evaluation.
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