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FACULTY

Christoph I. Lee, MD, MS, MBA
Professor, Radiology

Adjunct Professor, Health Sciences
Faculty Investigator,
Hutchinson Institute for Cancer Outcomes Research

University of Washington School of Medicine
Seattle, WA

 

 

 

 

Tuesday, February 5 | 2019

7:00pm Eastern | 6:00pm Central | 5:00pm Mountain | 4:00pm Pacific

 

Target Audience
A certified online lecture live with Dr. Christoph Lee intended for radiologists, nurses, and radiologic technologists

Format: Live Online Lecture
Credit:  1.0 AMA PRA Category 1

Credit:  1.0 ARRT Category A
Credit:  
1.0 ANCC Contact hour

Registration Fee: $10   (non-refundable)

ICPME is charging a nominal non-refundable registration fee for this webinar.

Why is this registration fee necessary?
Grant funds to support complimentary CME/CE/CNE are shrinking. ICPME continues to explore alternative ways to ensure new educational opportunities are available. We are very mindful of the fact that while grant funding is shrinking, the need for the education has not gone away.

We hope you will support us in keeping new educational opportunities available.

Lecture Overview
As the value of deep learning continues to find a foothold in breast imaging, reliance upon artificial intelligence for breast cancer screening will improve image interpretation accuracy 1,2,3 and equip doctors with a tool to decrease unnecessary breast biopsies.4

In addition to improved diagnosis, clinical, decision making, and improved patient outcomes, AI promises to be a valuable tool for radiology workflow. With the aid of AI, radiologists can spend more time interpreting studies and helping patients.5

  1. Ribli D, Horváth A, Unger Z, Pollner P, Csabai I. Detecting and classifying lesions in mammograms with Deep Learning. Sci Rep. 2018;8(1):4165.
  2. Artificial intelligence expedites breast cancer risk prediction. Imaging Technology News website. https://www.itnonline.com/content/artificial-intelligence-expedites-breast-cancer-risk-prediction Accessed April 26, 2018.
  3. Aboutalib SS, Mohamed AA, Berg WA, Zuley ML, Sumkin JH, Wu S. Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening [published online ahead of print October 11, 2018]. Clin Cancer Res. doi: 10.1158/1078-0432.
  4. Artificial intelligence expedites breast cancer risk prediction. Imaging Technology News website. https://www.itnonline.com/content/artificial-intelligence-expedites-breast-cancer-risk-prediction Accessed April 26, 2018.
  5. Mendelson EB. Artificial Intelligence in Breast Imaging: Potentials and Limitations. AJR Am J Roentgenol. 2018; 13:1-7.

Educational Objectives
At the conclusion of this activity, participants should be better able to:

  • Discuss the current status of artificial intelligence (AI) as it relates to breast cancer screening with mammography
  • Describe how AI will likely impact the daily practice of radiologists, including enhancement of image interpretation and subsequent reduction of unnecessary breast biopsies
  • In addition to image improved diagnosis, clinical, decision making, and improved patient outcomes, identify other areas in radiology where AI will have a significant impact

Joint Accreditation Statement

In support of improving patient care, this activity has been planned and implemented by the Postgraduate Institute for Medicine and International Center for Postgraduate Medical Education. Postgraduate Institute for Medicine is jointly accredited by the Accreditation Council for Continuing Medical Education (ACCME), the Accreditation Council for Pharmacy Education (ACPE), and the American Nurses Credentialing Center (ANCC) to provide continuing medical education for physicians.

Physician Continuing Medical Education
The Postgraduate Institute for Medicine designates this live activity for a maximum of 1.0 AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

The European Accreditation Council for CME (EACCME®)
The UEMS-EACCME® has mutual recognition agreements with the American Medical Association (AMA) for live event and e-learning materials.

For more information go to https://www.uems.eu/areas-of-expertise/cme-cpd/eaccme/mutual-recognition-with-the-united-states

Nurse Continuing Medical Education
The maximum number of hours awarded for this Continuing Nursing Education activity is 1.0 contact hours.

Radiologic Technologists
This program has been approved by the American Society of Radiologic Technologists (ASRT) for 1.0 hour of ARRT Category A continuing education credit.


How to Enroll and Participate
This program is offered by ICPME through the WebEx webinar service.

Registion Fee
The $10 registration fee includes access to the live online lecture and, upon verification of your full participation, a Certificate of Credit. ICPME accepts American Express, MasterCard, and Visa. No Checks.

Please note: The registration fee is non-refundable and can not be applied to another course.

  • Click ENROLL NOW and follow the registration instructions to register with ICPME.
  • You will receive an email from ICPME confirming your registration.
  • At the end of the registration process, click on ACCESS WEBINAR.
  • Detailed log-in instructions will be sent to you via e-mail the day before the webinar.

Credit Certificate
Credit cannot be granted for group viewing. To receive credit, each attendee must sign in on a separate computer.

  • To receive credit, each participant must attend the entire session and complete the postcourse evaluation within 7 days after the presentation.
  • Upon verification of your participation from the WebEx event report, you will receive an email from ICPME two weeks after the event with instructions to print your certificate of credit. You will not be able to print your certificate until that time.

Your certificate of credit will remain in your account at www.icpme.us as a permanent record of your participation.


Faculty
Christoph I. Lee, MD, MS, MBA

Dr. Christoph Lee is Professor of Radiology at the University of Washington (UW) School of Medicine, Adjunct Professor of Health Services at the UW School of Public Health, and Staff Physician at the Seattle Cancer Care Alliance. Dr. Lee’s research focuses on breast cancer screening technology assessment for which he has obtained grants from the National Institutes of Health, American Cancer Society, and Agency for Healthcare Research and Quality.

He is the lead or co-lead editor of five books spanning the basic sciences, evidence-based medicine, and medical imaging, distributed internationally by McGraw-Hill and Oxford University Press. Dr. Lee has authored or co-authored more than 150 peer-reviewed journal articles and chapters. He has served on the editorial boards of three leading specialty journals: Radiology, the American Journal of Roentgenology (AJR), and the Journal of the American College of Radiology (JACR).

Dr. Lee earned his BA cum laude from Princeton University, his MD cum laude from Yale University, and completed his radiology residency at Stanford University. He completed both a breast imaging fellowship and a two-year health policy fellowship as a Robert Wood Johnson Foundation Clinical Scholar at UCLA, where he earned his MS in health services research. Dr. Lee also earned his MBA in healthcare management from Johns Hopkins University with election to the Beta Gamma Sigma honor society.

Disclosure Information
Postgraduate Institute for Medicine (PIM) requires instructors, planners, managers and other individuals who are in a position to control the content of this activity to disclose any real or apparent conflict of interest (COI) they may have as related to the content of this activity. All identified COI are thoroughly vetted and resolved according to PIM policy.  The existence or absence of COI for everyone in a position to control content will be disclosed to participants prior to the start of each activity.

Christoph I. Lee, MD, MS, MBA, has disclosed receiving royalties from McGraw-Hill, Inc.; Oxford University Press; and UpToDate, Inc. He has also received consulting fees from the American College of Radiology and has provided contracted research for GE Healthcare. 

The PIM and ICPME planners and managers have nothing to disclose.

Disclosure of Unlabeled Use
This educational activity may contain discussion of published and/or investigational uses of agents that are not indicated by the FDA. The planners of this activity do not recommend the use of any agent outside of the labeled indications. 

The opinions expressed in the educational activity are those of the faculty and do not necessarily represent the views of the planners.  Please refer to the official prescribing information for each product for discussion of approved indications, contraindications, and warnings.

Questions?
For questions regarding this program, please contact ICPME:
Email: information@icpmed.com
Phone: 607-257-5860 x10


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Disclaimer
Participants have an implied responsibility to use the newly acquired information to enhance patient outcomes and their own professional development. The information presented in this activity is not meant to serve as a guideline for patient management. Any procedures, medications, or other courses of diagnosis or treatment discussed or suggested in this activity should not be used by clinicians without evaluation of their patient’s conditions and possible contraindications on dangers in use, review of any applicable manufacturer’s product information, and comparison with recommendations of other authorities.