Invention Grant
- Patent Title: Method for the computer-aided configuration of a data-driven model on the basis of training data
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Application No.: US16627562Application Date: 2018-06-07
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Publication No.: US11610112B2Publication Date: 2023-03-21
- Inventor: Thomas Engel , Alexander Michael Gigler
- Applicant: Siemens Aktiengesellschaft
- Applicant Address: DE Munich
- Assignee: Siemens Aktiengesellschaft
- Current Assignee: Siemens Aktiengesellschaft
- Current Assignee Address: DE Munich
- Agency: Schmeiser, Olsen & Watts LLP
- Priority: EP17179817 20170705
- International Application: PCT/EP2018/065029 WO 20180607
- International Announcement: WO2019/007626 WO 20190110
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
A method for the computer-assisted configuration of a data-driven model on the basis of training data is provided. The method is characterised in that the series of measurements are subjected to a suitable preprocessing process comprising a binning step, wherein measurement characteristics which existed during the measurement of the measurement values in question are taken into consideration. A suitable data-driven model such as a neural network is then learned on the basis of the pre-processed series of measurements. This learned data-driven model makes it possible to accurately forecast target vectors in accordance with associated series of measurements. The method can, for example, be used to analyse optical spectra. More particularly, it is possible to predict using the learned model whether the tissue sample for which an optical spectrum was detected represents diseased tissue.
Public/Granted literature
- US20200218972A1 METHOD FOR THE COMPUTER-AIDED CONFIGURATION OF A DATA-DRIVEN MODEL ON THE BASIS OF TRAINING DATA Public/Granted day:2020-07-09
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