Artificial intelligence 
in healthcare

Explore the basics of AI and what it means for healthcare

Begin with the basics of artificial intelligence.

Artificial intelligence (AI) is an emerging field that uses computers to understand human intelligence behavior, decision-making, and problem-solving.

This 7-minute educational video defines AI principles of machine learning and deep learning methods.

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Learn more about how AI works - (07:51)

Learn AI in simple terms through a series of short videos.

AI introduction and how it works - (01:00)

Explaining artificial neural networks - (00:52)

Demystifying artificial intelligence in healthcare

The application of AI in healthcare has many potential benefits to physicians, patients, and healthcare systems alike. Learn more about terminology to discover suitable applications of AI.

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What is an algorithm?

What is artificial intelligence and how does it work?

What is machine learning and how does it work?

What is deep learning and how does it work?

What is training data?

What is natural language processing and what are the applications in healthcare?

What is the difference between computer-aided detection and computer-aided diagnosis?

What are the benefits of AI in healthcare?

What are the misconceptions or limitations of AI?

How do we ensure the suitability of AI in healthcare?

Considerations for suitable artificial intelligence in healthcare

A detailed review of considerations will support the trust of an AI application and further confirm that it has value to clinical practice. AI will not replace physician decision-making; it is intended to enhance it.

Global report about
AI in healthcare

The World Health Organization (WHO) issued its first global report about AI in health. Learn about the six guiding principles:

  • Protecting human autonomy
  • Promoting human well-being and the public interest
  • Ensuring transparency, explainability, and intelligibility
  • Fostering responsibility and accountability
  • Ensuring inclusiveness and equity
  • Promoting AI that is responsive and sustainable

FDA identifies 10 guiding principles of machine learning.

The U.S. Food and Drug Administration (FDA), and others have issued a report with 10 guiding principles about Good Machine Learning Practice (GMLP). The principles from the report include:

  1. Multi-disciplinary expertise is leveraged throughout the total product life cycle
  2. Good software engineering and security practices are implemented
  3. Participants and data sets are representative of the intended patient population
  4. Training data sets are independent of test sets
  5. Selected reference datasets are based upon best available methods
  6. Model design is tailored to the available data and reflects the intended use of the device
  7. Focus is placed on the performance of the human-AI team
  8. Testing demonstrates device performance during clinically relevant conditions
  9. Users are provided clear, essential information
  10. Deployed models are monitored for performance and re-training risks are managed

MIT technology review insights

Produced in association with Medtronic

Advances in miniaturization and AI are enabling
the development of devices to help monitor
and treat chronic diseases.

Read article

More ways to learn about AI and connect

Perspective abstract

Physicians perspectives 

Find articles and clinical evidence about AI in GI.

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The future is now —
AI in gastroenterology

The benefits of GI Genius™ system introduces new possibilities in the field of endoscopy.

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Disclaimer: All content from healthcare professionals is their individual conclusions, unless otherwise cited. All speaker or author engagement for content is noted to acknowledge funding from Covidien LP, a Medtronic company, for any consulting engagement.