How deep learning is transforming healthcare

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Deep learning has been used to transform artificial intelligence (AI) development, whether it is from beating players in games like Go or poker to improving self-driving AI. But perhaps the most important changes for most of us is how AI advances and machine learning are affecting healthcare. In January, a medical startup won FDA approval for an AI-assisted cardiac imaging system called Arterys, and AI is playing vital roles in other health fields such as fighting cancer and aging. NVIDIA boasts that with deep learning, “AI can help doctors make faster, more accurate diagnoses. It can predict the risk of a disease in time to prevent it.”

These changes in healthcare will democratize the healthcare system, enabling ordinary citizens to obtain reliable health information. But this does not mean that doctors will become obsolete. Instead, doctors will work alongside AI as the two cover each other’s weaknesses, revolutionizing health care and saving lives.

Removing manual labor

To get an idea of how AI will change things, let us take a look at Arterys and how it uses AI. Arterys was developed by mining a data set of more than 3,000 cardiac cases where it looked at the heart and blood flow. By being hooked to a MRI machine, Arterys can examine blood flow and MRI images to generate editable contours. It can provide an accurate picture of a heart in seconds, a process which once took an hour.

Creating that accurate picture before required manual labor more than creative thinking, but that hour is now freed up by AI. Instead of taking the time to piece together MRI images, doctors can now come up with potential treatments while they leave this sort of manual labor to AI.

Read the source article at CIO.com