Cardiac surgery risk assessment system based on artificial intelligence

Through the artificial intelligence-based cardiac surgery risk assessment system integrating multimodal data acquisition, preprocessing, nonlinear modeling, data fusion, space-time synchronization, risk assessment and real-time feedback modules, the problems of data processing and space-time alignment in the existing technology are solved, efficient and accurate risk assessment and real-time feedback are achieved, and the safety of the surgery is improved.

CN119811681APending Publication Date: 2025-04-11MEI HOSPITAL UNIV OF CHINESE ACAD OF SCI
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Patent Information

Application Number
CN202411876798.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-19
Publication Date
2025-04-11

AI Technical Summary

Technical Problem

The prior art has problems with data type and format differences, noise processing and space-time alignment in cardiac surgery risk assessment. Traditional linear modeling methods cannot meet the needs of high-dimensional data analysis and are difficult to meet the requirements of real-time and accuracy.

Method used

A cardiac surgery risk assessment system based on artificial intelligence is proposed, and comprehensive and accurate risk assessment is achieved by integrating multimodal data acquisition, data preprocessing, nonlinear modeling, data fusion, space-time synchronization, risk assessment and real-time feedback modules. Specifically, it includes data acquisition, denoising, standardization, timing alignment, manifold learning dimensionality reduction, maximum entropy principle data fusion, space-time alignment of Liqun and Li algebra theory, machine learning risk assessment, and real-time feedback on Lyapunov stability theory.

Benefits of technology

It significantly improves the accuracy and reliability of cardiac surgery risk assessment, can respond to patients' physiological changes in real time, enhances the real-time and accuracy of evaluation results, reduces judgment errors caused by inconsistent data, and improves the safety of the surgery.

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Abstract

The invention relates to the field of medical treatment, and discloses a cardiac surgery risk assessment system based on artificial intelligence. The system fuses electrocardiogram, image data and physiological data of wearable equipment, and data quality is ensured through a data preprocessing module; carrying out data dimensionality reduction and nonlinear mapping by using manifold learning and the method, and capturing a relationship between complex physiological signals; the sensor weight is optimized by adopting the maximum entropy principle, and the accuracy of the evaluation result is improved; performing space-time alignment of the multi-modal data based on the Lie group and Lie algebra theories; modeling the fused data by using a machine learning algorithm to generate a risk assessment result; the real-time feedback module dynamically adjusts the evaluation model and system parameters, and the output module displays an evaluation result through a visual interface to assist doctors in accurate decision making. The system improves the accuracy and real-time performance of assessment, and provides scientific and comprehensive risk assessment support for cardiac surgery.
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