Google’s New Medical Imaging Suite Will Enable A Bright Future Ahead For Healthcare

Earlier this month, Google Cloud announced The new Medical Imaging Suite, the latest venture in the field of healthcare. This initiative builds on years of hard work by the Google Cloud team to create a universally easy-to-use, efficient, and value-providing platform along with an ode to interoperability and accessibility.

There are multiple applications behind the platform.

• Imaging storage: This suite enables a more comprehensive way to store and access advanced medical images
• Imaging lab: In partnership with chip maker NVIDIA, the platform makes it easy to automate routine imaging tasks, such as labeling.
• Image dataset and dashboard: The software utilizes advanced search tools to retrieve and display large amounts of data.
• Imaging AI pipeline: The suite is built to support artificial intelligence capabilities for integrating machine learning systems and models
• Imaging Deployment: The platform offers comprehensive and secure tools that can be curated to suit each organization’s needs

Thomas Kurian, CEO of Google Cloud, said: Before Explaining his overarching vision for the product line: By combining Google’s technological strength, backed by its unique scale and deep experience connecting its technology to consumer products and ecosystems, Google Cloud is able to put tomorrow’s tools in the hands of today’s organizations. I can do it. “

Established medical practitioners are already using this software. For example, Hackensack Meridian Health in New Jersey wants to use a robust suite for prostate cancer detection.

But integrating AI in healthcare and tackling the data problem is no easy task. Recently, many academics have voiced criticism that the so-called “digital revolution” in healthcare, particularly spurred by his Covid-19 pandemic, has not lived up to the lofty promises it promised. Instead, it has been difficult to integrate healthcare technology in meaningful ways, especially in ways that can actually impact patient care outcomes.

A lot of the challenges, especially with AI, is that you need a lot of data to create a training set to actually “teach” the AI ​​system how to interpret the data. In many organizations, data is unorganized, inaccessible, or remains in legacy formats that require extensive “cleanup” and reconciliation before it can be used in any meaningful way.

The goal of solutions like Google Cloud is to ultimately make data interoperable and ready for machine learning. This allows organizations to break away from the pre-information technology era. Whether healthcare professionals like it or not, healthcare is in the midst of a revolution that seamlessly integrates new and advanced technologies into patient care. Now it’s up to newly established technology leaders to make this revolution happen in a meaningful and secure way.