AI has the potential to revolutionize the field of genomic diagnostics. Healthcare Tech Outlook looks at how RCIGM has created a machine-learning based process that incorporates Natural Language Processing to rapidly and accurately diagnose genetic illnesses.
Artificial intelligence (AI) is revolutionizing genomic medicine by providing better health outcomes. BBN Times explores two applications of AI in genomic diagnostics, including RCIGM’s rWGS®.
Dr. Kingsmore joins the Precision Medicine Podcast to discuss the extraordinary role whole-genome sequencing is playing in prolonging and improving the life of critically ill newborns.
Rapid whole genome sequencing will become more useful, augmented by EHR data, the use of the cloud and comparisons with large databases, says Stephen Kingsmore, MD.
Babies with Fitz’s condition, commonly known as “bubble boy disease,” rarely survive to toddlerhood. He became one of the first babies anywhere to get a specific diagnosis within days of birth and an experimental therapy several months later that appears to have worked.
Project Baby Deer is allowing Bronson Children’s Hospital to diagnose genetic disorders in as fast as 30 hours; something that used to take nearly 30 days.
In 2021, the Genomic Medicine Working Group of the National Advisory Council for Human Genome Research of NHGRI identified its ten most significant peer-reviewed studies for 2021.
While it is safe to say that RCIGM has sufficiently proven its ability to identify the genetic variants driving many of these life-threatening rare conditions, it is now on a mission to bring its method of diagnosing sick babies to health systems across the country.
In its daily e-briefing for December 2, 2021, the Precision Medicine Institute reviewed the availability of Medicaid coverage for rWGS in Michigan, and the various state projects spearheaded by RCIGM that helped set the stage for Medicaid coverage.
While companies and investors have learned how to profit handsomely from rare diseases, they are still a healthcare desert to most people who suffer from them.