A desensitization management intelligent chip and method for rehabilitation follow-up data

By collecting user opinions and status data to assess privacy protection thresholds, segmenting data dimensions by features, evaluating value based on predictive models, and finding the optimal desensitization scheme, this approach solves the problems of unified rules, dynamic assessment of privacy protection thresholds, and neglect of data utility in the management of desensitization of rehabilitation follow-up data, achieving a balance between personalized privacy protection and data utility.

CN122417262APending Publication Date: 2026-07-17THE 901ST HOSPITAL OF THE CHINESE PEOPLES LIBERATION ARMY JOINT LOGISTICS SUPPORT FORCE
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
THE 901ST HOSPITAL OF THE CHINESE PEOPLES LIBERATION ARMY JOINT LOGISTICS SUPPORT FORCE
Filing Date
2026-04-28
Publication Date
2026-07-17

AI Technical Summary

Technical Problem

Existing desensitization management techniques for rehabilitation follow-up data have several problems, including: over-desensitization of high-value data due to uniform rule processing; lack of dynamic assessment of privacy protection thresholds; neglect of the actual utility of data in incremental model learning; and lack of optimization and seeking mechanisms in the generation of desensitization schemes.

Method used

The system employs a data collection and threshold assessment module to acquire user subjective opinions and objective status data, and uses an expert system to assess the privacy protection threshold value; a feature segmentation module divides the data into multiple dimensions; a value assessment module evaluates the value of data dimensions based on a predictive model library; and a strategy optimization module uses the privacy protection threshold as a constraint to find the optimal de-identification scheme that maximizes data utility and privacy protection performance.

Benefits of technology

It enables personalized and dynamic adjustments to privacy protection needs, refined quantification of data utility, and full release of data analysis value under the premise of privacy and security, providing an intelligent de-identification management solution for rehabilitation follow-up data.

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Abstract

本发明公开了一种康复随访数据的脱敏管理智能芯片及方法,涉及智能芯片技术领域。该方法包括:采集用户的原始康复随访数据、主观意见和客观状态数据,评估数据隐私保护门限值;对原始康复随访数据进行数据特征分割,确定多个数据维度;基于预测模型库中若干个预测模型的当前预测状态信息及历史样本训练集,对数据维度进行价值评估,确定多个数据维度价值系数;以大于数据隐私保护门限值为约束,以最大化数据效用和最大化隐私保护性能为目标,进行数据脱敏策略寻优,确定最优数据脱敏方案,并进行脱敏处理。本发明实现了康复随访数据的智能化脱敏管理,在保障用户隐私安全的前提下最大化了数据在模型增量学习中的效用价值。
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