Healthcare is turning out to be a potentially fertile ground for the application of artificial intelligence (AI). According to a report by Markets and Markets, application of AI in healthcare is expected to rise at a rapid annual pace of over 52% over the next five years, creating an $8 billion revenue opportunity.

One of the ways to tap into this multibillion-dollar opportunity is through NVIDIA (NVDA -6.80%), which is making impressive progress in this space with recent partnerships and contract wins. Let's take a look at how AI in healthcare could turn out to be a big business for the chipmaker.

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Latest partnerships will help NVIDIA tap the medical imaging opportunity

NVIDIA recently announced that it is partnering with healthcare solution provider GE Healthcare, a subsidiary of General Electric (GE -5.64%), and speech and imaging solutions provider Nuance Communications (NUAN). These two companies will use NVIDIA's AI platform in medical imaging applications.

GE Healthcare, for instance, will use NVIDIA's graphics processing unit (GPU) cloud to bring AI to 500,000 of its medical imaging devices across the globe. The two companies have together developed a new CT scan system known as Revolution Frontier CT, which can process medical images at twice the speed of its predecessor thanks to NVIDIA's AI platform.

As a result, this new system is expected to deliver more efficient and accurate clinical outcomes while detecting kidney and liver lesions, reducing the need for needless follow-ups and thereby improving patient care. According to NVIDIA, this is just one of the many benefits of using AI in medical imaging.

The chipmaker believes that "GPU-accelerated deep learning solutions can be used to design more sophisticated neural networks for healthcare and medical applications -- from real-time medical condition assessment to point-of-care interventions to predictive analytics for clinical decision-making." This will eventually help reduce the testing time, provide better images to doctors for diagnosis, and reduce the amount of radiation patients are subjected to thanks to the system's improved efficiency.

Nuance, on the other hand, has created an open AI marketplace for diagnostic imaging using NVIDIA's deep-learning platform. This marketplace will bring together developers, researchers, medical associations, healthcare companies, and hospitals on a single platform, creating a hub where radiologists can interpret a wide collection of medical images with the help of AI to create reports.

NVIDIA's platform will play a critical role in the training and publishing of AI applications on the platform, leading to faster and more accurate diagnosis and analysis of thousands of images. Now, Nuance's radiology reporting and medical image exchange network are used by 70% of radiologists in the U.S.

In all, AI-enabled medical imaging and diagnosis could generate more than $2.5 billion in revenue by 2024, according to Global Market Insights. This is no chump change as it represents almost 30% of the revenue generated by the chipmaker in the trailing 12 months. This space could substantial boost its revenue once the technology hits critical mass.

NVIDIA is moving deeper into healthcare

Medical imaging is just one of the application areas for AI in healthcare. GE Healthcare points out that just 3% of the 50 petabytes of data generated by a hospital annually is analyzed. AI can help make more of this data actionable in several other applications, such as creating treatment plans based on patient history or monitoring medication based on a patient's condition.

Not surprisingly, NVIDIA has decided to train a team of 100,000 developers in healthcare research, including critical areas such as cancer diagnosis. NVIDIA revealed that AI can help spot lung cancer sooner and could eventually save lives, as more than 80% of people affected by this disease die within five years' detection. This is because lung cancer symptoms appear only at advanced stages when a cure isn't possible, and early detection could triple survival rates.

This is where NVIDIA steps in with its Titan Xp GPUs, the Python Caffe deep-learning framework, and the CUDA parallel computing platform, helping data analytics start-up Innovation DX apply deep learning to train a neural network that could detect the presence or absence of lung cancer. Thanks to NVIDIA's Tesla GPU accelerators, Innovation DX's model can detect lung cancer with the help of 12,000 chest X-rays of confirmed lung cancer cases on the National Cancer Institute's database.

NVIDIA, therefore, is making the right moves in the healthcare market with the help of its artificial intelligence expertise. It has landed key clients in this space and is working to capitalize on critical areas such as cancer detection, which could give a significant boost to its business in the long run as AI deployment in healthcare gains steam.