- 专利标题: Machine learning techniques for hierarchical-workflow risk score prediction using multi-party communication data
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申请号: US17937190申请日: 2022-09-30
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公开(公告)号: US12061639B2公开(公告)日: 2024-08-13
- 发明人: Rajesh Sabapathy , Gourav Awasthi , Rebin Raju , Chirag Mittal , Sharenna D. Gonzalez
- 申请人: Optum Services (Ireland) Limited
- 申请人地址: IE Dublin
- 专利权人: OPTUM SERVICES (IRELAND) LIMITED
- 当前专利权人: OPTUM SERVICES (IRELAND) LIMITED
- 当前专利权人地址: IE Dublin
- 代理机构: Alston & Bird LLP
- 主分类号: G06F16/35
- IPC分类号: G06F16/35 ; G06F16/332 ; G06N20/00
摘要:
Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for performing predictive data analysis operations. Certain embodiments of the present invention utilize systems, methods, and computer program products that perform predictive data analysis operations by generating a hybrid class for a multi-party communication transcript data object associated with a predictive entity utilizing a hybrid space classification machine learning model, generating a machine learning-based risk score utilizing a hybrid-class-based risk scoring machine learning model, and generating a hierarchical-workflow risk score using a hierarchical risk score adjustment workflow.
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