Accelerating healthcare AI innovation with Zero Trust technology

From research to diagnosis to treatment, AI has the potential to improve outcomes for some treatments by 30 to 40 percent and reduce costs by up to 50 percent. Although healthcare algorithms are predicted to represent a $42.5B market by 2026, less than 35 algorithms have been approved by the FDA, and only two of those are classified as truly novel.1 Obtaining the large data sets necessary for generalizability, transparency, and reducing bias has historically been difficult and time-consuming, due in large part to regulatory restrictions enacted to protect patient data privacy. That’s why the University of California, San Francisco (UCSF) collaborated with Microsoft, Fortanix, and Intel to create BeeKeeperAI. It enables secure collaboration between algorithm owners and data stewards (for example, healthy systems, etc.) in a Zero Trust environment (enabled by Azure Confidential Computing), protecting the algorithm intellectual property (IP) and the data in ways that eliminate the need to de-identify or anonymize Protected Health Information (PHI)—because the data is never visible or exposed.

Enabling better healthcare with AI

By uncovering powerful insights in vast amounts of information, AI and machine learning can help healthcare providers to improve care, increase efficiency, and reduce costs. For example:

AI analysis of chest x-rays predicted the progression of critical illness in COVID-19 patients with a high degree of accuracy.2 An image-based deep learning model developed at MIT can predict breast cancer up to five years in advance.3 An algorithm developed at the University of California, San Francisco can detect pneumothorax (collapsed lung) from CT scans, helping prioritize and treat patients with this life-threatening condition—the first algorithm embedded in a medical device to achieve FDA approval.4

At the same time, the adoption of clinical AI has been slow. More than 12,000 life-science papers described AI and machine learning in 2019 alone.5 Yet the U.S. Food and Drug Administration (FDA) has only approved a little over 30 AI- and machine learning-based medical

This article is purposely trimmed, please visit the source to read the full article.

The post Accelerating healthcare AI innovation with Zero Trust technology appeared first on Microsoft | The AI Blog.

This post was originally published on this site