The following represents disclosure information provided by authors of this abstract. The program committee has reviewed all presenting author disclosure reports, identified potential conflicts of interest, and implemented strategies to manage those areas of conflict, where appropriate. All relationships are considered compensated. Relationships are self-held unless otherwise noted. I = Immediate Family Member, Inst = My Institution
 
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An unsupervised H&E-based machine-learning approach for precise prediction of tumor microenvironment subtypes.
 
Alexander Sarachakov
Employment - BostonGene
Stock and Other Ownership Interests - BostonGene
Patents, Royalties, Other Intellectual Property - BostonGene
 
Andrey Tyshevich
Employment - BostonGene
 
Anna Belozerova
Employment - BostonGene
Stock and Other Ownership Interests - BostonGene
Patents, Royalties, Other Intellectual Property - BostonGene
 
Ekaterina Postovalova
Stock and Other Ownership Interests - BostonGene
Patents, Royalties, Other Intellectual Property - Gene expression analysis techniques using gene ranking and statistical models for identifying biological sample characteristics; Techniques for determining tissue characteristics using multiplexed immunofluorescence imaging
 
Alexander Bagaev
Employment - BostonGene
Stock and Other Ownership Interests - BostonGene
Patents, Royalties, Other Intellectual Property - Patents for IP created In BostonGene
 
Vladimir Kushnarev
Employment - BostonGene
Stock and Other Ownership Interests - BostonGene
 
Nathan Hale Fowler
Employment - BostonGene
Leadership - BostonGene
Stock and Other Ownership Interests - BostonGene
Consulting or Advisory Role - Bayer; Celgene; Novartis; Roche/Genentech; TG Therapeutics; Verastem
Research Funding - Abbvie; BeiGene; Celgene; Gilead Sciences; Novartis; Roche; TG Therapeutics