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FDA REGULATIONS AND REQUIREMENTS FOR ARTIFICIAL INTELLIGENCE / MACHINE LEARNING

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🎤  José Mora     |  📅  October 18, 2022   |  🕒  11 AM Eastern Time US



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Why You Should Attend: 

It is not clear how to get AI/ML programs approved. The current regulatory
requirements don’t control AI/ML adequately. We will discuss the approaches FDA
is considering for regulation in the near future and how to get your AI/ML
program approved by the FDA now. Necessary submission documentation will be
explained. Attendees will receive a multipage outline and checklist. 

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DESCRIPTION:

AI/ML will revolutionize medicine by making diagnosis and treatment more
accessible and more effective. FDA has regulated medical software by means of
regulation and guidance for years, however, AI/ML programs fall outside the
scope of these regulations and guidance. This happens because the FDA approves
the final, validated version of the software. The point of AI/ML is to learn and
update the following deployment to improve performance. Thus the field version
of the software is no longer the validated approved version. 

We will discuss the current regulatory requirements, how they don’t control
AI/ML adequately, and approaches FDA is considering for regulation in the near
future. Your development program should conform to these concepts now because,
with some modifications, they will probably become regulations. Following a
discussion of possible future regulations, we will discuss, based on recently
approved De Novo applications, how to get your AI/ML program approved now.
Necessary submission documentation will be explained. This webinar is not a
programming course but will explain the present and future regulatory
requirements for AI/ML

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Areas Covered in the Session :

 * Required number of participants
 * Qualitative success criteria
 * Choice of tasks to validate
 * Post-test participant inquiry. Forms: Usability Validation Tracking Matrix
 * Validation Protocol
 * Validation Test Results Report will be given as Handouts



Who Should Attend:

 * Quality Assurance Departments
 * Research and Development Departments
 * Regulatory Affairs Departments
 * Engineering Departments
 * Software Engineers
 * Marketing Departments
 * IT Departments
 * Management Teams









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FDA Artificial Intelligence Machine Learning
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