Displaying results 1 - 4 of 4
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A machine-learning algorithm to identify hepatitis C in health insurance claims data
Content Type: Abstract
Hepatitis C virus (HCV) infection is a leading cause of liver disease-related morbidity and mortality in the United States. Monitoring the burden of chronic HCV infection requires robust methods to identify patients with infection. Insurance claims… read more -
Comparing Cerebral Palsy Surveillance Definition to ICD Codes and Written Diagnoses
Content Type: Abstract
Cerebral Palsy (CP) is the most common cause of motor disability in children. CP registries often rely on administrative data such as CP diagnoses or International Classification of Diseases (ICD) codes indicative of CP. However, little is known… read more -
Rapid classification of autism for public health surveillance
Content Type: Webinar
This presentation given August 3, 2017 describes work toward applying machine learning methods to CDC’s autism surveillance program. CDC’s population-based autism surveillance is labor-intensive and costly, as it requires clinicians to manually… read more -
Human-learned lessons about machine learning in public health surveillance
Content Type: Webinar
Presented December 13, 2018. For public health surveillance, is machine learning worth the effort? What methods are relevant? Do you need special hardware? This talk was motivated by these and other questions asked by ISDS members. It will focus… read more