Nurses lack awareness of recent advances in AI that can help provide personalized healthcare. The following presentation aims to narrow this practice gap by providing education on the possibilities and limitations of using AI in healthcare.
Accreditation Statement: University of Texas at Austin School of Nursing is accredited as a provider of nursing continuing professional development by the American Nurses Credentialing Center's Commission on Accreditation.
Requirements for Successful Completion: To receive contact hours for this continuing education activity, the participant must complete the entire online module and complete and submit the evaluation form. Once the evaluation form has been submitted, a “Certificate of Successful Completion” will be awarded for 1.0 contact hours and will be available in your Learning Express account under "View/Print CE Credit".
Learning outcome: Registered nurses will report desire to change practice related to knowledge increase regarding empowering patients to use health technology to address chronic disease self-management. Focus will be on challenges specific to the aging population, youth, and underserved populations, exploring digital health research possibilities and limitations within the framework of ethical and legal boundaries.
The activity’s Nurse Planner has determined that no one who has the ability to control the content of this CNE activity – planning committee members and presenters/authors/content reviewers – has a conflict of interest.
This activity expires May 1, 2024
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Fee
$20.00
CE Hours
1.00
CE Units
0.100
Activity Type
- Knowledge
Target Audience(s)
- Registered Nurses
- Researchers
Nurses lack awareness of recent advances in AI that can help provide personalized healthcare. The following presentation aims to narrow this practice gap by providing education on the possibilities and limitations of using AI in healthcare.
Speaker(s)/Author(s)
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Joydeep Ghosh
Brief Bio : Joydeep Ghosh, PhD, is currently the Schlumberger Centennial Chair Professor of Electrical and Computer Engineering at the University of Texas, Austin. He also serves as the Chief Scientist of Cognitive Scale, which was selected in 2018 to be among the 61 technology pioneers worldwide by the World Economic Forum, among other recognitions. Dr. Ghosh's research interests lie primarily in data mining and web mining, responsible AI, scalable machine learning algorithms, specially for predictive and prescriptive analytics, and applications to a wide variety of complex real-world problems, including health informatics. |
Release Date:
May 1, 2022
Credit Expiration Date:
May 1, 2024
CE Hours
1.00
Fee
$20.00