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How AI & Machine Intelligence is Assisting Clinicians

Artificial intelligence (AI), or machine intelligence, is being integrated into many facets of healthcare. One of these sectors is clinical imaging analysis. AI is also being embedded in algorithms inside medical devices.

machine intelligence

Download the full report.

Why imaging analysis? Most likely the wide usage — whether you’re a diagnostician, radiologist, or oncologist, much of your time is still spent looking at medical images, and writing up reports or patient files about them. And some 80 percent of AI activity in clinical imaging is on image analysis.

According to a new Ovum white paper, sponsored by NVIDIA, there is a huge opportunity to help physicians with AI-based systems that can cut down on the workload across protocoling, imaging analysis, and automated reporting of the results.

The new report, “Enhancing Diagnostic Quality and Productivity with AI,” explores how AI is assisting doctors in a wide variety of areas, including protocoling. According to the report, protocoling could be a potential target for AI systems, as well as report generation and quantification, which also take up a lot of these professionals’ time.

This white paper hones in on how AI can assist radiologists, in particular. One of the ways AI is being used is for lesion detection and searching for lesions in images — a time consuming activity that has created extensive backlogs at radiology offices in the past.

“There is a high potential for AI systems to assist radiologists going through these backlogs, assisting physicians to be more productive and help improve accuracy,” the report states.

Many of today’s advanced scanning instruments have GPUs installed, which makes embedding AI algorithms or neural network architectures like deep learning onto the systems easier. Companies like GE Healthcare, Siemens Healthcare and Esaote use NVIDIA GPUs for visualization, helping accelerate scanned images by processing the magnetic resonance signals, ultrasound, or x-ray data streams.  

This report delves into a variety of advances in clinical imaging being introduced through AI and machine intelligence.

The end goal could be an integrated system that replaces much of the legacy equipment and assists in: performing scans, analyzing images and producing reports through one connected solution.

That said, machine intelligence is not designed to replace medical experts, but rather assist them in serving their patients more efficiently. The report points out that some medical researchers are even proposing that AI is the step that will make quality individual treatment, or personalized healthcare, possible at scale.

The full white paper covers the following topics:

  • Why Radiologist plus AI
  • The Rise of Machine Intelligence and its Role in Healthcare
  • Benefits of AI Applied to Imaging
  • Market Overview in AI Imaging Analysis and Diagnostics
  • NVIDIA’s Role in AI and Healthcare

Download the new NVIDIA report, “Enhancing Diagnostic Quality and Productivity with AI,” to learn how AI can reduce the burden on radiologists and improve the quality of medical imaging.

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