AI Series: Introduction to Clinical Data


AI Series: Introduction to Clinical Data Banner



Date & Location
Thursday, August 10, 2023, 12:00 AM - Sunday, August 9, 2026, 11:59 PM, On Demand

Overview

Internet Enduring Material Sponsored by Stanford University School of Medicine. Presented by the  Center for Health Education at Stanford University School of Medicine. Observational data are collected in healthcare systems during routine clinical activities. Intelligent big data platforms and AI technologies are necessary to improve the quality and transition of healthcare by expediting investigation of active hidden factors in clinical data with machine learning algorithms to obtain actionable gap-based information about patients. This course teaches you how the observational data can be used to answer important clinical research questions.


Registration

  Original Release Date: August 10, 2020
  Review Date: August 8, 2023
  Expiration Date: January 7, 2027
  Estimated Time to Complete: 11.0 hours

Click Begin (at the top) to learn more about how to enroll in the course.

View entire series: https://www.coursera.org/specializations/ai-healthcare


Credits
AMA PRA Category 1 Credits™ (11.00 hours), Non-Physician Participation Credit (11.00 hours)

Target Audience
Specialties - Non-clinical
Professions - Advance Practice Nurse (APN), Allied Dental Professional, Athletic Trainer, Counselor, Dentist, Dietetic Technician Registered (DTR), Fellow/Resident, Industry, Non-Physician, Nurse, Nurse Anesthetist (CRNA), Occupational Therapist, Optometrist , Pharmacist, Pharmacy Technician , Physical Therapist, Physician, Physician Associate, Psychologist, Registered Dietitian, Registered Nurse (RN), Social Worker, Student

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

  1. Determine how observational data can answer potential clinical research questions
  2. Review the major sources and types of healthcare data used to support machine learning
  3. Determine the importance of time and the use of healthcare data
  4. Utilize the desired data-driven shape analysis

Accreditation

In support of improving patient care, Stanford 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 education for the healthcare team. 

Credit Designation

American Medical Association (AMA)
Stanford Medicine designates this Enduring Material for a maximum of 11.00 AMA PRA Category 1 CreditsTM. Physicians should claim only the credit commensurate with the extent of their participation in the activity.


Additional Information

Cultural and Linguistic Competency
The planners and speakers of this CME activity have been encouraged to address cultural issues relevant to their topic area for the purpose of complying with California Assembly Bill 1195. Moreover, the Stanford University School of Medicine Multicultural Health Portal contains many useful cultural and linguistic competency tools including culture guides, language access information and pertinent state and federal laws.  You are encouraged to visit the Multicultural Health Portal: http://lane.stanford.edu/portals/cultural.html

Reference/Bibliography List
For additional resources, please visit the course.

For activity related questions, please contact
  Ph: 650.204.3984
  Email: [email protected]

For CME general questions, please contact 
   Ph: (650)-497-8554
   Email: [email protected]