Our proprietary and advanced AI platform uses the largest existing dataset of tumor profiling results, matched with clinical outcomes, to identify new cancer subtypes with specifically defined molecular signatures.
DEAN creates and validates dozens of machine learning proprietary signatures to provide the most in-depth and exclusive analysis and interpretation. DEAN learns from patient data, including what patients were treated with and their outcomes, and uses a non-linear feature selection to find relevant associations in the cast informatic space that our profiling generates.
Caris Next Generation Profiling™, which is powered by DEAN, identifies unique molecular signatures by cancer subtype to help predict which patients may respond to specific treatments, making clinical assessment more precise. This has the potential to improve cancer diagnosis and therapeutic guidance in ways never before possible.
DEAN enables MI GPS™ (Genomic Profiling Similarity) Score, a proprietary algorithm that molecularly classifies cancer into dozens of distinct molecular subtypes that refine and improve current diagnostic standards and informs more personalized and precise treatment.
Caris Next Generation Profiling (NGP) uses the power of DEAN (Deliberation Analytics) artificial intelligence and machine learning technology to provide oncologists with the most thorough molecular analysis classification to inform decision making.
Caris GPSai™ technology has been demonstrated to accurately identify tumor origin using molecular information. This is especially important to provide an unequivocal result when there is ambiguity about tissue of origin. The use of Caris GPSai technology with machine learning algorithms will help to understand non-linear relationships at the molecular level to improve cancer diagnosis and treatments tailored molecular subtype.
Caris is at the intersection of science, medicine and information.
Connecting patients with the most up-to-date and relevant clinical trials.