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Your Partner in Biomarker Discovery

High Parameter Flow Cytometry
See our process
Take a look at how we Survey cells through a 30+ color analysis
Use cases
Common requests we process through this service
Color navigation
Proof of concept
Process designing
Equipment testing
Biomarker banking
Voltage walking
Service Overview
Centuries ago, people died primarily due to wars, disease, and low levels of living standards and medical care. Today, chronic diseases are the main threat to longevity, and the reality of modern medicine is that there are many more patients than doctors who are able to help them. Health monitoring systems provide multiple options to change the traditional management of patients, reduce the cost of health care, and help hospitals improve their treatment processes. The global patient monitoring devices market is expected to reach over $73 billion by 2028, with significant growth attributed in part to technological advancement in patient monitoring devices.
Pipeline Architecture
Below we can see a sample of raw device monitoring event data. In its current form, measurement data is nested inside an array, making it difficult to monitor the change in their values over time. By using one or more Decodable pipelines, which are streaming SQL queries that process data, we can transform the raw data into a form that is best suited for how it will be consumed.

Aggregate Data Stream
Below we can see a sample of raw device monitoring event data. In its current form, measurement data is nested inside an array, making it difficult to monitor the change in their values over time. By using one or more Decodable pipelines, which are streaming SQL queries that process data, we can transform the raw data into a form that is best suited for how it will be consumed.

Experiences
Leave your experimenting to those that perform with precision and care
Conclusion
As we can see from this example, a sophisticated business problem can be addressed in a very straight-forward way using Decodable pipelines. It is not necessary to create docker containers, there is no SQL server infrastructure to set up or maintain, all that is needed is a working familiarity with creating the SQL queries themselves.

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