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Blog
Aidoc Staff

The Challenge of Data Deluge: Will AI Sink or Swim?

aiOS, Data Management, System Integration
Table of Contents

Patient data is increasingly voluminous in today’s age of digitized healthcare. The problem is this data is often unstructured, making it difficult to derive high-value, actionable insights. 

This segment of our whitepaper, The Clinical AI Scorecard: How Different Integration Approaches Handle Deployment Challenges, gives a brief overview of this very problem. Click here to download Pt. I of the whitepaper and learn about the benefits of an AI platform for implementation and deployment.

Unreliable and Unstandardized Data

A significant portion of healthcare data is unstructured, meaning it lacks a predefined format or organization. This includes narrative clinical notes, radiology reports and patient-generated data. 

Unstructured data is challenging to process and analyze using traditional methods, making it difficult to extract valuable insights for AI algorithms. For instance, a pulmonary embolism algorithm needs to analyze all chest CT exams with contrast, but this information is not always consistent in the metadata. 

A common solution is to manually define a new series of instructions or guidelines for each scan – commonly referred to as protocols – but this approach is not scalable due to the sheer number. Additionally, as protocols change, the rules and formatting of metadata also changes, which creates more and more patient data that must be sorted and analyzed. This highlights the importance of data governance and the need to effectively utilize metadata. Below is a quick look at the popular AI integration options operating in this context: Point Solutions, Marketplaces and Platforms.

Learn more about the power of clinical AI platforms and how they can help transform data into action. Click here to download our whitepaper. 

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