PRESENTER(S)
Bradley J. Erickson, MD, PhD
PRESENTER BIO
Dr. Erickson serves as medical director for the Office of Artificial Intelligence in the Center for Digital Health. He holds the academic rank of professor of radiology Mayo Clinic College of Medicine and Science.
Dr. Erickson’s research interests include computer-aided diagnosis and the use of computer technologies to extract information from medical images for diagnostic, prognostic and therapeutic purposes. This research includes the development and validation of algorithms that can detect progression, regression or risk of disease, and the prediction of molecular markers from medical images. He is also actively developing a system to promote team science, initially pursuing imaging-focused research, but with connections to genomics, pathology and clinical data.
LEARNING OBJECTIVES
Upon conclusion of this activity, learners should be able to:
- Demonstrate the current technology and capabilities of Deep Learning applied to imaging
- Recognize the strengths and weaknesses of Deep Learning methods as they are applied to medicine
- Assess the potential for AI to improve the precision of care provide to patients
ATTENDANCE / CREDIT
Text the session code (provided only at the session) to 507-200-3010 within 48 hours of the live presentation to record attendance. All learners are encouraged to text attendance regardless of credit needs. This number is only used for receiving text messages related to tracking attendance. Additional tasks to obtain credit may be required based on the specific activity requirements and will be announced accordingly. Swiping your badge will not provide credit; that process is only applicable to meet GME requirements for Residents & Fellows.
TRANSCRIPT
Any credit or attendance awarded from this session will appear on your Transcript.
For disclosure information regarding Mayo Clinic School of Continuous Professional Development accreditation review committee member(s) and staff, please go here to review disclosures.
QUESTIONS?
Contact Coordinator Chris Scott 507-284-0426

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