Frost and Sullivan has estimated the Artificial Intelligence (AI) Market for Healthcare IT in 2018 for hospitals at $574 million USD and expects it to grow at a CAGR of 65 percent to $4.3 billion USD in 2022! Similar explosive growth is predicted across other segments of healthcare. Machine Learning (ML) is a type of AI that has already seen successful application in healthcare, particularly rapid growth, and shows major untapped potential to further help improve healthcare going forward. Key use cases range from resource and asset optimization to readmission prevention, chatbots, anti-fraud, behavioral analytics, medical risk analytics, claims analytics, cybersecurity, and many more. Business values driving healthcare organizations to deploy AI solutions across these use cases span cost reduction, improving patient outcomes, and improving the engagement and experiences of patients and healthcare professionals. Major opportunities for startups range from creating AI products and solutions for specific use cases and healthcare needs to services for education, customizing AI solutions, integrating them with existing enterprise systems and data stores, managing and operating solutions, and so forth. See the AI in Healthcare Guide for more information on these use cases and opportunities.

Below I review key goals of any healthcare AI startup, and how Microsoft Azure empowers startups to both meet their goals and maximize the benefits of AI to the healthcare organizations they serve.

Run lean

With finite funding, all startups are looking to run lean, maximize their runway (how long the startup can survive if income and expenses stay constant) and their ability to achieve success. The major way to run lean is by avoiding capital expense of data center equipment, and expensive IT and cyber security staff (Azure has numerous built-in security measures — see Azure Security). Microsoft Azure enables you to acquire just the right amount of data center capability you require and address it as an operating expense, rather than a capital expense. You can also focus your limited resources on creating your AI solution versus building, securing, and managing low-level data center infrastructure. Microsoft Azure enables you to start free, and supports a wide range of open source technologies including a wide variety of tools such as Node.js to multiple operating systems from Ubuntu, to Debian, SUSE, and more.

Start quickly

With any compelling idea, there is a finite window of opportunity, and time is of the essence for any startup, especially those in AI where innovation is moving at a brisk and accelerating pace. With Microsoft Azure you can deploy web apps and Virtual Machines (VMs) in seconds. Furthermore, rather than start your cloud at zero with a blank slate, you can bootstrap your solution in Microsoft Azure with blueprints that include example code, test data, automated deployment, documentation, and security and compliance support. This approach gets you a working reference solution in your Microsoft Azure cloud, and 50-90 percent towards your end solution. From that beginning, you can get started on your pilot as soon as possible and rapidly close the gap to your end solution. See the AI in healthcare blueprint with HIPAA and HITRUST security and compliance support for further details.

Stay agile

Startups move quickly, learn fast, and must be able to pivot rapidly to keep competitive. Microsoft Azure provides agility for your AI solution, enabling you to make changes and scale with point-and-click efficiency using your secure, powerful web-based dashboard for managing your cloud environment.

Grow fast, go big

Microsoft Azure provides support for startups at every stage of their growth, from technology enablement to exploration, to business growth through accelerators and venture funding, and connecting you with customers. With Azure you can also scale worldwide to 34 regions globally, supported by Azure’s industry-leading law and regulatory compliance framework support. For more on Microsoft’s commitment to startups see the announcement Grow, build, and connect with Microsoft for Startups:

“We are committing $500 million over the next two years to offer joint sales engagements with startups, along with access to our technology, and new community spaces that promote collaboration across local and global ecosystems. Startups are an indisputable innovation engine, and Microsoft is partnering with founders and investors to help propel their growth,” said Charlotte Yarkoni, Corporate VP, Growth and Ecosystems at Microsoft.

Getting started

For much more on how to partner with Microsoft to power your healthcare AI startup to success see the Azure for Startups, which includes multiple case studies and success stories.

Further resources

1. AI in Healthcare Use Cases Guide
2. AI in Healthcare Solutions Guide
3. AI in Healthcare Blueprint

Collaboration

What other use cases, challenges, solutions, and opportunities for startups are you seeing for AI in healthcare? We welcome any feedback or questions you may have below. AI in healthcare is a fast-moving field. New developments are emerging daily. Many of these new developments are not things you can read about yet in a textbook. I post daily about these new developments and solutions in healthcare, AI, cloud computing, security, privacy, and compliance on social media. Reach out to connect with me on LinkedIn and Twitter.