Liquid biopsy is revolutionizing precision oncology with its non-invasive approach. In this blog, we explore its clinical applications and why the right analytical technologies are needed when searching in a sea of genomic data.
Deep learning-based approaches to genomic instability assessment can help overcome the limitations of current methods and maximize insights from tumor samples.
This guide deciphers the jargon associated with machine learning in healthcare and explains why artificial intelligence is invaluable to revolutionize the capabilities of HCPs in improving patient care.
SOPHiA GENETICS™ is excited to be a part of the Healthcare Information and Management Systems...
Learn about the SOPHiA DDM™ Platform’s CNV detection algorithm from our Senior Algorithm Researcher, Bita Khalili.
Third party sequencing services can enable increased access to NGS testing, but if institutions do not receive access to the raw data it can limit the insights they can gain. Doing the data analysis in house can allow you to harness the power of genomic data to reveal relevant variants.
Q&A with the Clinical Application Product Manager, Mikhail Pertziger, PhD
Learn about the technology behind the SOPHiA DDM™ Homologous Recombination Deficiency (HRD) Solution from the lead developer, Dr. Christian Pozzorini.
Radiomics maximizes upon information that’s already being collected. The difference is how that info is used.
Think of it like trying to find a treasure buried on a beach. It would be a lot easier to use a metal detector than to pick through each grain of sand.
Humans being replaced by computers is a common theme in TV shows, movies, books and more. But unlike what we often see in fiction, artificial intelligence (AI) doesn’t replace the human factor in medicine.
To measure results from one individual against those of a control group and those with similar genomic profiles, data analysis must be unconditionally repeatable.