In Brief AI in medicine is changing healthcare as we know it. The introduction of deep learning systems is only possible by powerful computing capabilities; capabilities that Nvidia has made possible with their graphic processors. A New Age of Healthcare Artificial intelligence is slowly making its way into the realm of modern healthcare. Googles DeepMind is revolutionizing eyecare in the United Kingdom, and IBMs Watsonis tackling cancer diagnosticson par with human physicians. Both AI systems use deep learning, a concept loosely mirroring how our own brains work by having AI software analyze exorbitant amounts of data and uncover patterns which is particularly applicable in diagnostics.
As medical imaging technology continues to take advantage of every new deep learning breakthrough, the challenge is that the computing technology on which it relies must evolve just as quickly. A company called Nvidia is leading that charge under the guidance ofKimberley Powell, who isconfident that Nvidiasprocessors are not only meeting the deep learning standards of medical imagining, but also pushing the industry forward as a whole.
Nvidias hardware has established its silent but prominent role in deep learnings marriage with medicine. Powell believes projects like their specializedcomputers, such asthe DGX-1a powerful deep-learning product, will become increasingly more common in hospitals and medical research centers. Strongcomputing power, like what the DGX-1 can provide, stands to increase thereliability of the diagnostic process; something that, in turn, wouldsignificantly boost thestandard of care in developing countries.
While AI wont be replacing doctors anytime soon, it will provide physicians with tools tomore efficiently and reliably assess patients.AI is already involved in mining medical data, diagnosing medical images, studying genomics-based data for personalized medicine, and improving the lives of the disabled.
Thanks to NVIDIAs DGX-1, hospitals can efficiently compare a single patients tests and history with data from a vast population of other patients. Some medical research centers and startups are automating the analysis of MRIs, CT scans, and X-rays to assist physicians inmaking a diagnosis. Others are utilizing deep learning to create genetic interpretation enginesto identify cancer-causing mutations in patient genomes, bringing to life the concept of personalized medicine.
However, while AI will no doubt continue torevolutionize medicine for years to come, physicians often find themselves perplexed byhow to incorporate the technology into their regular practice. Only onceAI is accepted, and fully integrated, into medicinewill we see the full potential for the technology in terms of lending itself to more efficient and accurate diagnostics from routine checkups to more specialized fields.
Read more:
Artificial Intelligence is Completely Transforming Modern Healthcare - Futurism
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