Bridging the gap between healthcare today and healthcare tomorrow requires machine learning. Find out how ML solves healthcare claims processing problems.
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Bridging the gap between healthcare today and healthcare tomorrow requires machine learning. Find out how ML solves healthcare claims processing problems.
In automation, using that most derided approach—the template—can be useful, but it has its limitations with the best and worst discussed here.
Explore if and when templates are useful in Intelligent Capture and how machine learning is used for highly variable documents or unstructured documents.
Enterprises created a work-from-anywhere environment and events went exclusively online so when we attended intelligent capture webinars, many of us had the same questions, answered here.
How to configure your Intelligent Document Processing (IDP) software so it does what you want it to by leveraging truly intelligent capture.
Is there such a thing as machine learning that does NOT require training on sample data? The answer is “sort of” – find out why here.
Every organization with complex processes can benefit from automation by automating manual processes to reduce effort, but how do you do that for core processes?
Find out about Intelligent Document Processing (IDP) strategies and shortcuts for what amount of data is satisfactory and how to get there.
Now that Software-defined Intelligent Document Processing (IDP) is here, is gathering input data really that big of a problem? Find out here.
The age of software-defined Intelligent Document Processing is here. Find out what this means for your organization.
Here’s a dirty, little secret about IDP software vendor claims and how to truly automate document-oriented tasks.
Ontology is the latest buzzword in the intelligent capture solution domain. Sounds cool. But what does it mean? Does it really change things for the better?