Real Life Business Impact of AI/ML on GE CT Scanners Using Glassbeam Clinsights™

Vivek Sundaram
Sep 25, 2019

We are now in an era where machine learning isn't just hype. In fact, it is absolutely real in its business impact as Glassbeam has recently demonstrated for its growing network of connected medical imaging equipment.

With Glassbeam's extensive experience in data engineering and analytics related to GE CT Scanner machine logs, we now have dozens of powerful use cases where automated anomaly detection via machine learning has been used to detect potentially expensive part failures well before the end-user even noticed an issue.  Here are 3 real-world examples:

Clinsights Software Opens New Frontiers of Collaboration between Radiology and Clinical Engineering groups; Saving Hundreds of Thousands of Operations’ / Capital Dollars

Vivek Sundaram
Jun 18, 2019

For the first time in the Healthcare industry, two distinctly different groups in a healthcare provider organization come under the eye of a single pane of glass. The roles are Clinical Engineering practitioners responsible for machine uptime and other is the Radiology and Imaging groups responsible for maximizing machine utilization and therefore revenues.  The common goal is always improving patient care and clinical outcomes for the benefits of its customers.

Who Owns the Data – Part 2

Puneet Pandit
May 16, 2019

In Part 1 of this blog series, I set the stage to understand who owns the machine data generated by medical devices such as CT, MRI, and so on. We also discussed how the restrictions on device data evolved over time and the implications on healthcare providers’ maintenance programs.

2018 Recap and Looking Forward to Growth in 2019

Puneet Pandit
Jan 30, 2019

2018 was a defining year for Glassbeam. We blazed the trail through the year signing up 15 customers and pilot sites located at Scripps Health, Grossmont Imaging, Eisenhower Health, and several more. As we head into the second month of 2019, we just announced a key partnership that is all set to take the VA Healthcare market by storm.

Glassbeam Q3 Highlights: Expanded Partnerships, Solution Capabilities and HIPAA Compliance

Puneet Pandit
Oct 03, 2018

We are now three-quarters of the way through 2018 and very proud of our team’s many accomplishments this year. From new offerings and partnerships to certifications and industry event participation, we have made great strides towards our goal of expanding our advanced analytics offerings to include support for more healthcare equipment types and manufacturers.

Redefining Art of Analyzing Medical Machine Logs: Glassbeam Q2 Milestones and Momentum

Puneet Pandit
Jul 17, 2018

Most would consider analytics a science. The Glassbeam team considers analytics an art of combining impermeable truth from machine logs with deep healthcare domain expertise.  As we expand our penetration of the healthcare market after spending years in the data center world, where the gold standard for machine uptime was 99.999 percent, we have recognized a huge opportunity since the acceptable machine uptime for medical equipment ranged from 90 to 97 percent.

Data Doesn’t Lie: 5 Ways Hospitals Can Use Machine Log Data

Pawan Jheeta
Jul 04, 2018

Maximizing uptime of diagnostic equipment is vital to both patients and healthcare organizations. As medical imaging equipment becomes more sophisticated and the need for healthcare organizations to improve their availability becomes more acute, so does the value of machine log data and advanced analytics. Here, we’ve listed several important ways that hospitals can use machine log data and predictive/prescriptive analytics to optimize operational efficiency and revenues.

7 Must Have Items on Your Checklist Before You Consider Machine Data Analysis

Vijay Vasudevan
Jun 05, 2016

These are the 7 key factors that highlight whether performing machine data analysis realizes credible value for you.

1. Prepare the raw data —

Most of machine data are in the form of logs. Industrial machines are constantly producing valuable operational data (call-home data) on configuration, performance, usage, and other important parameters that define the very life of the device in the field.

Geting the most out of akka clusters

Aug 14, 2015

Anyone serious about distributed systems or building one, commonly encounters issues such as replication, consistency, availability and partition tolerance (CAP) [1]. In a real life scenario, partition tolerance is inevitable. So the system must be able to handle partition tolerance when there are network outages. Therefore, ‘P’ in the CAP is a must for any distributed system. This has been backed by Peter Deutsch in his (EIGHT FALLACIES OF DISTRIBUTED COMPUTING).

What the spark!

Feb 13, 2015

No, we don’t hate Spark! We like it a lot – regular blog readers know that we integrated Apache Spark’s MlLib library into our SCALAR product last Fall. If you missed this news, here’s the PRESS RELEASE and BLOG POST.