Udemy – ISO 14971 Risk Management for AI/ML Medical Devices 2024-10
Published on: 2024-11-06 19:32:44
Categories: 28
Description
ISO 14971 Risk Management for AI/ML Medical Devices course. This training course will help you fully understand the application of AAMI/BSI TR 34971 and ISO 14971 standards in the risk management of AI-based medical devices. In this course, you will learn how these global frameworks ensure safety, regulatory compliance, and quality throughout the product lifecycle. Focusing on AI-specific challenges such as algorithmic bias, model drift, and data integrity, participants will gain valuable insights into mitigating the risks associated with AI technologies in healthcare. This training course will comprehensively help you to get acquainted with the principles and methods of risk management in medical devices based on artificial intelligence. By participating in this course, you will be able to produce safer, higher quality medical devices in accordance with global standards.
What you will learn in the ISO 14971 Risk Management for AI/ML Medical Devices course
- Understanding Risk Management Specific to AI in Medical Devices: You will learn how to identify and manage the unique risks that exist in AI-based medical devices.
- Understanding the legal requirements for AI-based medical devices: You will learn about the laws and regulations related to AI-based medical devices.
- Implement a comprehensive risk management process: You will be able to develop a comprehensive process for risk management in AI-based medical devices.
- Identify and mitigate AI-specific risks: You will learn how to identify and mitigate AI-specific risks such as algorithmic bias and model bias.
- Ensure post-sale monitoring and continuous improvement: You will learn how to monitor and continuously improve the performance of post-sale AI-based medical devices.
This course is suitable for people who
- Legal Affairs Professionals: Individuals working in medical device compliance who need to understand the application of ISO 14971 and AAMI/BSI TR 34971 standards to manage AI-specific risks and ensure regulatory compliance.
- Quality Assurance and Risk Management Professionals: Professionals responsible for ensuring the safety, quality, and performance of medical devices will benefit from learning how to implement a comprehensive risk management process for AI-based medical devices.
- Medical device developers and engineers: Engineers and developers involved in creating or updating AI-based medical devices will gain important insights into how to identify and mitigate AI-specific risks such as algorithmic bias and model bias.
- Health and AI Enthusiasts: People interested in AI and healthcare innovation who want to learn about the intersection of AI technology with medical device legislation, safety standards, and risk management.
ISO 14971 Risk Management for AI/ML Medical Devices course specifications
- Publisher: Udemy
- Lecturer: eQMS Innovation
- Training level: beginner to advanced
- Training duration: 1 hour and 4 minutes
- Number of courses: 13
Course headings
ISO 14971 Risk Management for AI/ML Medical Devices course prerequisites
- Basic Understanding of Medical Devices and AI Learners should have a foundational understanding of medical devices and how artificial intelligence (AI) is used in healthcare applications. Familiarity with basic AI concepts, such as machine learning models and their applications, is helpful but not mandatory.
- Familiarity with Risk Management Principles Some experience with risk management or quality assurance processes (in any industry) would be beneficial. This includes concepts like risk assessment, mitigation strategies, and compliance.
- Eagerness to Learn No prior experience with ISO 14971 or AAMI/BSI TR 34971 is required. Beginners are welcome, and the course will cover all key concepts, standards, and practices needed to understand and manage risk in AI-based medical devices.
Course images
Sample video of the course
Installation guide
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download link
Download file – 338 MB
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File size
338 MB
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