Abstracts due February 2, 2024
The 2024 NKBDS Conference invites abstracts highlighting the innovative use of artificial intelligence or data to advance the practice and understanding of the nursing profession. Concepts could include the use of data and/or artificial intelligence to:
- Show the value of nursing care and/or nursing documentation.
- Inform the optimization of clinical decision support and/or the use of standards (including standard terminologies).
- Utilize emerging technologies such as large language models in direct nursing care, care management, executive leadership or patient engagement and outcomes measurement.
- Highlight the value of nursing informatics and/or the acquisition of informatics competencies on the nursing workforce, to include impact on workforce engagement, retention, satisfaction, and burnout.
- Outline work in progress with potential future implications and/or review completed work with lessons learned (both successes and failures), to include opportunities and challenges for the future.
Please submit abstracts via this link ONLY and upload your Word document by February 2, 2024, at 11:59 pm Central Time. Questions and clarifications can be directed to email@example.com (do not submit abstracts to the email address). Abstracts will be peer-reviewed and authors will be notified of the outcome by March 1, 2024.
All accepted abstract authors will be invited to present a poster and/or participate in Q&A during the abstract presentation session.
Abstracts will have the option to be published as an appendix of the 2024 Nursing Knowledge Big Data Science Conference Proceedings.
Abstracts should include the following items and be submitted as a Microsoft Word (*.doc) document:
- Author(s) full name, degree(s), institution, city, state, country (if applicable)
- Learning Objectives
- Introduction or Description of the Problem
- Methods or Description of the Solution
- Results or Impact on Clinical Practice
- Discussion and Conclusions
- References (AMA Style)
Abstracts should be submitted in Times New Roman, 12-point font, single spaced. Your abstract should be a maximum of one single-spaced page, exclusive of tables/figures and/or references. All tables/figures should be referenced in the text and legends should explain the content.
Please submit abstracts via this link ONLY and upload your Word document by February 2, 2024, at 11:59 pm Central Time.