There is a new IDC report1 that’s a good primer on AI best practices in healthcare, and it identifies NetApp as a provider to emulate. Called “Realize the Transformative Power of AI for Healthcare with NetApp Solutions,” it gives useful background information and explains why organizations need to implement AI now or risk falling behind.
The 11-page report covers the technical basics for evaluating an AI system, offering sound guidance on key components. It also gives examples of innovative companies that are using AI to solve real-world healthcare problems. IDC correctly points out that from genomics to medical imaging, there is so much potential for AI across many areas of healthcare.
But IDC also acknowledges that AI has not always lived up to its hype. There has been a large percentage of deployment failures, often due to cost and decision criteria. In other words, it’s not usually the technology’s fault but human decisions.
Top Factors Holding Back AI Deployments n = 2,473 Base = all respondents Source: IDC's Global Artificial Intelligence Survey, 2019
IDC recommends that to succeed, companies should first look at their datasets, because “data is foundational to AI.”
“The development of AI solutions that deliver meaningful and actionable insights in real-world conditions require high-quality and quantity of data. Clinical data sets are complex and large,” IDC writes.
As a result, companies should expect that AI initiatives require a scalable, high-performing architecture to handle the workloads.
“The NetApp AI Control Plane is NetApp’s full-stack AI data and experiment management solution,” IDC says. “It provides extreme scalability, streamlined deployment, and nonstop data availability—when and where you need it.”
NetApp AI Control Plane But the proof rests in successful implementations, IDC writes, and this is where NetApp really separates itself from the field.
“NetApp AI solutions have successfully accelerated AI algorithms and applications design and deployments for leading healthcare organizations globally and delivered scalable, consistent, and high-performing architecture,” IDC says. NetApp customer King’s College London is featured as an example case study of a customer using the NetApp AI solution for radiology/pathology.
At NetApp, we have been working hard to deliver the right AI solutions for our customers. Different use cases require different approaches, but the benefits of AI tend to be universal: better insights, faster speed to market, and improved patient outcomes.
IDC agrees that AI has become essential for healthcare. It notes that by 2024, AI-powered enterprises will respond 50% faster than their peers to everything—customers, competitors, regulators, and partners.
Although different healthcare areas are maturing at different rates, virtually all segments hold promise for AI.
“AI is a true competitive differentiator; it improves business agility and accelerates time to market with newer products and services,” IDC says.
NetApp® AI solutions are primarily based on two main components:
Mike McNamara is a senior leader of product and solution marketing at NetApp with 25 years of data management and data storage marketing experience. Before joining NetApp over 10 years ago, Mike worked at Adaptec, EMC and HP. Mike was a key team leader driving the launch of the industry’s first cloud-connected AI/ML solution (NetApp), unified scale-out and hybrid cloud storage system and software (NetApp), iSCSI and SAS storage system and software (Adaptec), and Fibre Channel storage system (EMC CLARiiON). In addition to his past role as marketing chairperson for the Fibre Channel Industry Association, he is a member of the Ethernet Technology Summit Conference Advisory Board, a member of the Ethernet Alliance, a regular contributor to industry journals, and a frequent speaker at events. Mike also published a book through FriesenPress titled "Scale-Out Storage - The Next Frontier in Enterprise Data Management", and was listed as a top 50 B2B product marketer to watch by Kapos.
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