Invention Grant
- Patent Title: Sequential minimal optimization algorithm for learning using partially available privileged information
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Application No.: US16782573Application Date: 2020-02-05
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Publication No.: US11531851B2Publication Date: 2022-12-20
- Inventor: Kayvan Najarian , Jonathan Gryak , Elyas Sabeti , Joshua Drews
- Applicant: THE REGENTS OF THE UNIVERSITY OF MICHIGAN
- Applicant Address: US MI Ann Arbor
- Assignee: THE REGENTS OF THE UNIVERSITY OF MICHIGAN
- Current Assignee: THE REGENTS OF THE UNIVERSITY OF MICHIGAN
- Current Assignee Address: US MI Ann Arbor
- Agency: Marshall, Gerstein & Borun LLP
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G16H50/50 ; G06N20/10

Abstract:
Computational algorithms integrate and analyze data to consider multiple interdependent, heterogeneous sources and forms of patient data, and using a classification model, provide new learning paradigms, including privileged learning and learning with uncertain clinical data, to determine patient status for conditions such as acute respiratory distress syndrome (ARDS) or non-ARDS.
Public/Granted literature
- US20200250496A1 SEQUENTIAL MINIMAL OPTIMIZATION ALGORITHM FOR LEARNING USING PARTIALLY AVAILABLE PRIVILEGED INFORMATION Public/Granted day:2020-08-06
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