NVIDIA partners with Scripps to develop digital health AI
The Scripps Research Translational Institute is partnering with graphics firm NVIDIA to develop AI and deep learning best practices, tools and infrastructure to develop AI applications using genomic and digital health sensor data.
With NVIDIA, California-based research organisation Scripps will establish a centre of excellence for artificial intelligence in genomics and digital sensors.
Scripps and NVIDIA will work to advance the use of machine learning and deep learning to harness the exploding quantity of health data.
The partnership will focus on data generated by faster, more affordable genome sequencing gear, and digital health sensors such as smartwatches, blood pressure cuffs and glucose monitors.
NVIDIA AI experts and Scripps researchers and clinicians will use deep learning and machine learning, to tackle the deluge of genomics and sensor data.
Genomics data is doubling every seven months. To keep up, the team will develop deep learning approaches to help improve mutation detection and make genome sequencing more affordable and accessible.
The growth in genomics data is why the use of the data-hungry deep learning approach in genomic research papers has increased 40 times in the last four years.
Eric Topol, the institute’s founder and director, said: “AI in medicine has tremendous promise.
“Eventually, it will markedly improve accuracy, efficiency, and workflow in medical practice with the potential to lower cost. But so much of this depends on validating AI algorithms and proving clinical efficacy. The data inputs from sensors and sequencing, in particular, will play an important role.”
Topol leads a team focused on individual medicine that’s part of the larger Scripps Research Institute, ranked by Nature last year as the world’s most influential research institution on innovation.
Earlier this year, the UK government announced that Topol will lead a review of how the NHS can best use AI and robotics, as well as technologies such as genomics and digital medicine.
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