Medical imaging or diagnostic equipment such as Computed Tomography (CT), Ultrasound, and Magnetic Resonance Imaging (MRI) devices play a critical role in modern healthcare. But while these devices enable healthcare providers to better diagnosis their patients' and provide an optimal treatment plan, they are also very expensive to maintain.
In this section we will investigate how Glassbeam’s DSL called SPL (Semiotic Parsing Language) helps in parsing multi-structured machine logs.
SPL allows a log file to be treated as a hierarchical document consisting of multiple segments (or sections). Each hierarchical segment is called namespace. This allows for zeroing in on the exact section to parse specific elements from, thus localizing the scope of extracts.
The Association for the Advancement of Medical Instrumentation (AAMI) Conference and Expo is a big stage for conversations about innovation, advancements and security for medical equipment. Our team recently attended the 2018 expo in Long Beach, CA, and we were thrilled to mingle with like-minded industry professionals who share our interests in the advancement of medical instrumentation.
Glassbeam’s business revolves around providing business intelligence on machine data. Intelligence comes from structured data. Machine data is not always structured. So, there is a gap between what is needed and what is produced. As Glassbeam’s head of engineering, I am going to write a two series blog about how Glassbeam bridges this gap.
Capital expenditures for healthcare equipment totaled more than $350 billion in 2016, according to Harbor Research. Healthcare organizations and Independent Service Organizations (ISOs) are now turning to AI and machine learning to predict and prevent equipment failures and reduce operational costs.
Predictive analytics can be used to reclaim millions of dollars in operational costs for healthcare organizations.
As pressure mounts to lower healthcare costs, healthcare delivery organizations are taking a closer look at costs in all aspects of their business, particularly operations. More organizations are realizing there is a huge opportunity to lower operational costs by leveraging machine data and machine learning.
Glassbeam loves its customers. Customer development is an integral part of Glassbeam. Our healthcare/clinical customers are telling us how the newly launched Glassbeam CLinical Engineering ANalytics (CLEAN) Blueprint is creating immense value by analyzing machine log data and presenting deep insights about machines in their clinical environment.
We are exhibiting at MD Expo April 4-6, a leading high tech medicine (HTM) trade show and conference. It will be held at the Renaissance Nashville Hotel, 611 Commerce Street. We hope you will stop and visit us at booth #119.