Democratizing Clinical Insights with Machine Data Analytics

Glassbeam is at the forefront of the revolution disrupting the status-quo with its AI/ML and Expert Rules Platform to analyze machine data from imaging and biomedical assets to help increase machine uptime and utilization, leading to increased patient throughput, revenues, and reduced operational costs.


of providers claim to have no “automated” visibility into their fleet wide utilization


of clinical engineering leaders are experiencing 60-70 hours downtime per machine per year


of the providers are facing over 10% revenue leakage from their patient referral network

Solutions for Clinical Engineering Departments

  • Single pane of glass to manage health and status of all key modalities (MR, CT, Cathlab) for key manufacturers (GE, Siemens, Philips)
  • Perform remote login and access connected assets to better understand the real issues at a facility/machine, become proactive versus reactive in solving issues
  • Allow machine learning to take over and alert you proactively on helium levels, cold head temperature, magnet pressure, scan counts, aborts, and arcs for MRI and CT modalities
  • Gain insights from environmental sensor data collected near real-time from the hospital environment including compressor Power, Room temp/humidity, and Chiller water temp In/Out.

Solutions for Radiology and Imaging Leaders

  • Gain actionable insights to improve patient throughput and revenues from your entire imaging fleet by analyzing exam statistics per facility, per machine, and per operator
  • Perform ‘what-if’ analysis on key metrics such as “change-over-time” and see the impact on improved fleet utilization that will directly translate to more revenues
  • Track business flowing in from all your referring physicians and get alerted when the certain group falls below a threshold or have large no-shows
  • Analyze reject exam frequency by facility and operators and understand how to fix the root cause by knowing reject reasons, leading to better operator training, and so on.

Solutions for C-suite and budgeting decision makers

  • Before approving new purchases, login anytime anywhere to our cloud-based app to get consolidated fleet-wide utilization data broken by facilities, manufacturers, and machine types
  • Get benchmark information on the utilization of facilities, machines, and operators, by exam types, to ask the right questions when making important decisions
  • Request custom analysis as weekly, monthly or quarterly reports, delivered in slides and/or pdf to your inbox for your Board Room presentations

Solutions for Biomedical Engineers - Dig Deeper Into Issues

  • Perform remote login and access connected assets to better understand the real issues at a facility/machine, become proactive versus reactive in solving issues
  • Log into Glassbeam Explorer to search for error patterns on MR, CT, Cathlab log data – find answers and save “search expressions” in a common knowledge base library to share with your peers
  • Build expert rules based on your expertise gained from years of industry experience and tribal knowledge, set thresholds when you want to be alerted, on emails or text

Integrate your CMMS Data with Machine Data Insights

  • Import key metrics from your CMMS system on a daily basis into Glassbeam, combine with machine data alerts and create a unified view of machine health information
  • Auto-create new cases in your CMMS system and assign to key field engineers, based on critical errors and warnings flagged by Glassbeam AI/ML platform, and allow your staff to become proactive versus reactive
  • Mine historical case data and case notes leveraging NLP algorithms in Glassbeam platform to create new expert rules in Glassbeam platform to expand the centralized knowledge base

Use Cases for Healthcare Provider Organizations

Powered by Machine Learning, Glassbeam provides rich analytics to increase uptime and improve fleet utilization of healthcare equipment.

System Health

Enables service engineers to define complex rules on machine logs by uncovering error prone patterns and signatures that help service engineers decrease time to issue resolution.

Predict Tube Failures

A predictive model on a combination of overheating, image artefacts, scanning errors, mA out of range, mA out of range, hardware warning results in effective tube failure prediction.

Forecast Cooling Issues

Track and forecast on external cooling parameters Magnet pressure, Helium level, Cold head temperature & duty cycle, Water flow and temperature, Compressor power, Gantry temperature.

Anomaly Detection

Track all system metrics and build statistical anomaly detection on Tube arcs/spits, Filter move errors, Gantry, rail, plenum temperatures, Fan speed, Packets drops, and Collimator errors.