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Despite adoption hurdles, healthcare is all-in on Generative AI

CIO

Generative AI (GenAI) is having a renaissance, but few industries are experiencing this like healthcare. Despite the rosy outlook, it doesn’t paint the full picture of GenAI in healthcare. The 2024 Generative AI in Healthcare Survey , however, does a better job at that. This article will explore the main findings.

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The future of healthcare: Why enterprises must embrace AI innovation

CIO

The intersection of AI, software, and data management is set to revolutionize healthcare and will serve as a critical driver of medical innovation and improved patient outcomes. The pivotal role of AI in healthcare From clinical applications to operational efficiencies, AI is already having a significant impact on the healthcare industry.

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How to advance healthcare data interoperability with Microsoft Cloud

CIO

IT leaders have long been aware of the benefits that data interoperability creates, both internally and with external healthcare entities. Yet despite years of work and regulatory mandates, today’s healthcare ecosystem is still marked by data trapped in stand-alone systems. But there’s good news.

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Use cloud computing to accelerate GenAI adoption in healthcare with Microsoft AI

CIO

Certain healthcare organizations have been slow to embrace cloud computing despite its proven benefits, largely due to security concerns. But cloud caution will also likely hinder the healthcare sector’s adoption of Generative AI (GenAI) applications. The cloud is designed for exactly such demands.

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Use Cases for Apache Cassandra®

From understanding its distributed architecture to unlocking its incredible power for industries like healthcare, finance, retail and more, experience how Cassandra® can transform your entire data operations.

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Three key areas where healthcare IT leaders can deploy AI to improve patient outcomes

CIO

Healthcare providers face formidable challenges in applying AI capabilities to patient care. Healthcare IT leaders can begin using AI tools and capabilities to improve patient outcomes now. Healthcare IT leaders can begin using AI tools and capabilities to improve patient outcomes now. For example, the U.S.

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Insights from Middle Eastern CIOs: AI’s transformative impact on healthcare

CIO

In recent years, the healthcare industry has undergone a remarkable transformation propelled by technological advancements, reshaping the landscape of patient care and medical practices. One of the most significant contributions of AI to healthcare lies in its ability to revolutionize diagnostics and disease management.

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Using Data & Analytics for Improving Healthcare Innovation and Outcomes

In the rapidly evolving healthcare industry, delivering data insights to end users or customers can be a significant challenge for product managers, product owners, and application team developers. The complexity of healthcare data, the need for real-time analytics, and the demand for user-friendly interfaces can often seem overwhelming.

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The New Tech Experience: Innovation, Optimization, and Collaboration

Speaker: Paul Weald, Contact Center Innovator

No matter what industry you're in - healthcare, customer service, sales, and more - it’s easier than you think to reduce wait times, monitor sentiment, and provide enhanced self-service options for all of your users. Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence!

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Data Science Fails: Building AI You Can Trust

AI has the power to transform countless industries — including the healthcare, banking, insurance, and public service sectors, to name just a few — by introducing new efficiencies and revealing new opportunities for companies to solve problems.

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A PM’s Guide to Forging an Outcome-Driven Product Team

Speaker: Kim Antelo, Transformation Coach

In this webinar, Transformational Coach Kim Antelo will walk through a case study of a healthcare company with lofty OKRs, but with little tie-back to the product performance. The best product teams evaluate themselves not by the quantity or speed with which they release new features, but by how much those features add value.