Patent ID: 11935152
Assignee: TEMPUS LABS, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 17:
18. A non-transitory computer-readable medium comprising a set of computer-executable instructions that, when executed by one or more processors, cause a computer to:
process a plurality of segmented tile images each corresponding to a different respective portion of a digital image of a Hematoxylin and Eosin-stained slide of a target tissue using a deep learning framework by:
(i) predicting a respective biomarker classification for each tile image using one or more trained biomarker classification models; and
(ii) predicting a respective tissue classification for each tile image using one or more trained deep learning classifier models;
determine, based on (i) and (ii), a predicted presence of one or more biomarkers in a target tissue;
transmit the predicted presence of the one or more biomarkers;
receive a molecular training dataset for a plurality of training tissue samples, the molecular training dataset comprising molecular data based on sequencing of a substantially similar sample associated with each training tissue sample; and
identify one or more molecular data subsets in the molecular training dataset, each corresponding to a different respective biomarker, by processing the molecular training dataset using a clustering algorithm.