Difference between revisions of "Improper Payments"
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<b>Implementation Case Study Using AI to Reduce Improper Payments | <b>Implementation Case Study Using AI to Reduce Improper Payments | ||
− | </b><br>This award-winning project at the Centers for Medicare and Medicaid Services utilizes a combination of AI tools to expedite the intake and validation of medical records. Recognized by the 2019 Government Innovation Awards and ACT-IAC's 2019 Igniting Innovation Awards, this project has generated a significant return on investment since going live in April 2019. This session explored the solution development process, technologies harnessed, and the project’s results to date. Payam Mousavi, Director, Government Intelligent Automation, KPMG | + | </b><br>This award-winning project at the Centers for Medicare and Medicaid Services utilizes a combination of AI tools to expedite the intake and validation of medical records. Recognized by the 2019 Government Innovation Awards and ACT-IAC's 2019 Igniting Innovation Awards, this project has generated a significant return on investment since going live in April 2019. This session explored the solution [[development]] process, technologies harnessed, and the project’s results to date. Payam Mousavi, Director, Government Intelligent Automation, KPMG |
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Revision as of 14:00, 17 March 2023
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Improper Payments
- https://federalnewsnetwork.com/artificial-intelligence/2020/07/machine-learning-could-reduce-improper-cares-act-payments/ Machine learning could reduce improper CARES Act payments | Tom Temin - Federal News Network]
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