Machine Learning Data Framework

ASCEND®’s commitment to data governance and integrity has resulted in a level of data quality unmatched in our industry. 

Machine Learning Data Framework

ASCEND’s cardiovascular data framework is an ideal choice for any organization seeking to train and validate clinically relevant Machine Learning (ML) algorithms that rely, in whole or in part, on cardiovascular data. With hundreds of hospitals using ASCEND cardiovascular structured reporting over the course of twenty years, ASCEND’s customers have amassed millions of procedure reports representing an enormous repository of detailed, clinically accurate cardiovascular data associated with images and waveforms. In building and managing the underlying cardiovascular data schema, ASCEND’s commitment to data governance and integrity has resulted in a level of data quality unmatched in our industry. 

In addition to building structured reporting, imaging, and clinical collaboration software, ASCEND has developed targeted ML algorithms to facilitate cardiovascular workflow. As a result, our team understands the challenges and pitfalls faced by ML developers working in the clinical medicine space. 

ASCEND’s goal is to assist healthcare organizations and vendors to unlock the latent potential in archived cardiovascular data and help turn innovative ML concepts into reality. By partnering with ASCEND, we can: 

  • Apply our clinical expertise and clinical informatics knowledge to identify the cardiovascular data required to address your specific needs and goals 
  • Assist in extracting this data and transforming it into a data repository tuned for ML development 
  • Indicate where the most relevant data repositories for your needs can be found 
  • Evaluate and validate the results of your machine learning efforts 

 

ASCEND has worked effectively with both large and small partners over many years. Let us help you turn your Machine Learning ideas into reality. For more information, contact us at information@ascendcv.com or call 844-413-2610. 

or call (844) 413-2610

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