- Patent Title: System to identify and explore relevant predictive analytics tasks of clinical value and calibrate predictive model outputs to a prescribed minimum level of predictive accuracy
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Application No.: US16531189Application Date: 2019-08-05
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Publication No.: US11651289B2Publication Date: 2023-05-16
- Inventor: Bryan Conroy , Junzi Dong , Minnan Xu
- Applicant: KONINKLIJKE PHILIPS N.V.
- Applicant Address: NL Eindhoven
- Assignee: Koninklijke Philips N.V.
- Current Assignee: Koninklijke Philips N.V.
- Current Assignee Address: NL Eindhoven
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N3/08 ; G06N20/00

Abstract:
A method of implementing a task complexity learning system, including: learning a model for predicting the value of a continuous task variable y based upon an input variable x; learning an encoder that encodes a continuous task variable y into an encoded task value; calculating a loss function based upon the predicted value of y output by the model and the encoded task value output by the encoder; calculating a distortion function based upon the input continuous task variable y and the encoded task value, wherein learning the model and learning the encoder includes minimizing an objective function based upon the loss function and the distortion function for a set of input training data including x, y pairs.
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