diff --git a/README.md b/README.md index be72882d..f8fe02b3 100644 --- a/README.md +++ b/README.md @@ -8,10 +8,11 @@ - [2.1 Privacy Standard Notice](#21-privacy-standard-notice) - [2.2 Records Management Standard Notice](#22-records-management-standard-notice) - [2.3 Domestic Copyright Protection Notice](#23-domestic-copyright-protection-notice) -- [2.4 Open Source Notice](#24-open-source-notice) -- [2.5 License Standard Notice](#25-license-standard-notice) -- [2.6 Github Notice](#26-github-notice) -- [2.7 Contributing Standard Notice](#27-contributing-standard-notice) +- [2.4 Public Domain Standard Notice](#24-public-domain-standard-notice) +- [2.5 Open Source Notice](#25-open-source-notice) +- [2.6 License Standard Notice](#26-license-standard-notice) +- [2.7 Github Notice](#27-github-notice) +- [2.8 Contributing Standard Notice](#28-contributing-standard-notice) [3. General Disclaimer](#3-general-disclaimer) @@ -27,15 +28,6 @@ Please see the [UserGuide](/docs/user_guide.md) to get a technical overview of t The exchange of public health data is hindered by outdated, manual processes. Some state, local, tribal, and territorial health departments still rely on fax, email, and physical mail to receive case data, requiring staff to manually review and re-enter information from lab reports. This labor-intensive process can take up to 20 minutes per report, and electronic data extraction remains cumbersome and error-prone, particularly when handling multiple documents. As a result, low accuracy in data ingestion impedes the ability of public health departments to efficiently process and utilize critical health data. -## Public Domain Standard Notice -This repository constitutes a work of the United States Government and is not -subject to domestic copyright protection under 17 USC § 105. This repository is in -the public domain within the United States, and copyright and related rights in -the work worldwide are waived through the [CC0 1.0 Universal public domain dedication](https://creativecommons.org/publicdomain/zero/1.0/). -All contributions to this repository will be released under the CC0 dedication. By -submitting a pull request you are agreeing to comply with this waiver of -copyright interest. - ## The Solution ReportVision is a powerful tool designed to automate the reading and extracting of data from lab reports, helping public health departments streamline their workflows. Leveraging the power of the Tesseract engine and Microsoft Azure Cloud Platform, ReportVision allows teams to create customizable, data-driven templates for automatic extraction and annotation of multiple datasets—delivering notable accuracy and speed. @@ -50,7 +42,7 @@ Check out the following videos to see how the updated OCR model works in action,