Artificial intelligence in healthcare: a primer for medical education in radiomics

Author:

Waldman Carly E1ORCID,Hermel Melody2ORCID,Hermel Jonathan A3,Allinson Francis1,Pintea Mark N4,Bransky Natalie5,Udoh Emem1,Nicholson Laura6,Robinson Austin7,Gonzalez Jorge7,Suhar Christopher8,Nayak Keshav9,Wesbey George7,Bhavnani Sanjeev P10ORCID

Affiliation:

1. Division of Internal Medicine, Scripps Clinic, La Jolla, CA 92037, USA

2. Division of Cardiology, Scripps Clinic, La Jolla, CA 92037, USA

3. Medical Student, Tulane University School of Medicine, New Orleans, LA 70112, USA,

4. Medical Student, California University of Science & Medicine, Colton, CA 95757, USA,

5. Medical Student, University of California, San Diego School of Medicine, San Diego, CA 92037, USA

6. Associate Program Director for Resident Research, Division of Internal Medicine, Scripps Clinic, La Jolla, CA 92037, USA

7. Advanced Cardiovascular Imaging, Divisions of Cardiology & Radiology, Scripps Clinic, La Jolla, CA 92037, USA

8. Fellowship Program Co-Director, Division of Cardiology, Scripps Clinic, La Jolla, CA 92037, USA

9. Director, Structural Heart Program, Division of Cardiology, Scripps Mercy, San Diego, CA 92037, USA

10. Principal Investigator Healthcare Innovation & Practice Transformation Laboratory, Division of Cardiology, Scripps Clinic, La Jolla, CA 92037, USA

Abstract

The application of artificial intelligence (AI) to healthcare has garnered significant enthusiasm in recent years. Despite the adoption of new analytic approaches, medical education on AI is lacking. We aim to create a usable AI primer for medical education. We discuss how to generate a clinical question involving AI, what data are suitable for AI research, how to prepare a dataset for training and how to determine if the output has clinical utility. To illustrate this process, we focused on an example of how medical imaging is employed in designing a machine learning model. Our proposed medical education curriculum addresses AI’s potential and limitations for enhancing clinicians’ skills in research, applied statistics and care delivery.

Funder

Scripps Health

Publisher

Future Medicine Ltd

Subject

Pharmacology,Molecular Medicine,General Medicine

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