Machine learning and AI in medicine – Part 1

For years relegated to science fiction, as exemplified when the HAL 9000 had a speaking role in 2001: A Space Odyssey, artificial intelligence (AI) now has become practical reality and in medicine, a long-hoped-for remedy in areas from pathology to electronic medical records. Yet, artificial intelligence, which encompasses machine learning and other functions, has limitations. In this episode, learn about the current state of artificial intelligence and what it can realistically achieve for your practice.

 

Guest speaker:

Shannon Sims, MD, PhD

Vice President

Data Intelligence and Interoperability

Vizient

 

Moderator:

Tomas Villanueva, DO, MBA, FACPE, SFHM

Associate Vice President

Clinical Resources

Vizient

 

Show Notes

[00:56] Understanding concepts around AI

[02:28] Two main functions of AI

[03:33] Importance of prescriptive analytics

[04:26] Enabling clinicians make better decisions

[05:13] Machine learning and EMRs

[06:10] AI and the coronavirus

[07:52] Structural challenges

[09:01] AI and quality

[10:09] Role of clinicians in developing solutions

[11:04] Successes and limitations

 

Links | Resources:

Machine Learning in Medicine (NEJM—April 4, 2019) Click here

HYPE Randomized Clinical Trial Click here

Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data (JAMA Internal Medicine—Nov 2018) Click here

On Deep Learning for Medical Image Analysis (JAMA—Sept 18, 2018) Click here

Artificial Intelligence in Health Care: Will the Value Match the Hype? (JAMA—June 8, 2019) Click here

Artificial Intelligence in Health Care: A Report from the National Academy of Medicine (JAMA—Feb 11, 2020) Click here

Artificial Intelligence: Promise, Pitfalls and Perspective (JAMA—June 23/30, 2020) Click here

 

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