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machinelearningsolutions.com

Machine Learning Solutions

A major challenge in healthcare applications has always been the clustering of providers (physicians, labs, DME suppliers, etc.) based on the mix of medical services performed and diagnoses treated. A typical problem will involve billions of claims from hundreds of thousands of providers, who utilize tens of thousands of codes for services and diagnoses. A hierarchical clustering problem with this many entities and variables had previously resisted any efficient solution. It soon became apparent that Per...

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Gene D'Angelo

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Gene D'Angelo Consulting

Gene D'Angelo

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A major challenge in healthcare applications has always been the clustering of providers (physicians, labs, DME suppliers, etc.) based on the mix of medical services performed and diagnoses treated. A typical problem will involve billions of claims from hundreds of thousands of providers, who utilize tens of thousands of codes for services and diagnoses. A hierarchical clustering problem with this many entities and variables had previously resisted any efficient solution. It soon became apparent that Per...
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Machine Learning Solutions | machinelearningsolutions.com Reviews

https://machinelearningsolutions.com

A major challenge in healthcare applications has always been the clustering of providers (physicians, labs, DME suppliers, etc.) based on the mix of medical services performed and diagnoses treated. A typical problem will involve billions of claims from hundreds of thousands of providers, who utilize tens of thousands of codes for services and diagnoses. A hierarchical clustering problem with this many entities and variables had previously resisted any efficient solution. It soon became apparent that Per...

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Machine Learning Solutions

A major challenge in healthcare applications has always been the clustering of providers (physicians, labs, DME suppliers, etc.) based on the mix of medical services performed and diagnoses treated. A typical problem will involve billions of claims from hundreds of thousands of providers, who utilize tens of thousands of codes for services and diagnoses. A hierarchical clustering problem with this many entities and variables had previously resisted any efficient solution. It soon became apparent that Per...

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