Difference between revisions of "SoN LAI 4 Day Intensive May 2022"

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==Challenges==
 
==Challenges==
  
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| align="center" style="background:#f0f0f0;"|'''Data, Methods & Implementation  Challenges'''
 
| align="center" style="background:#f0f0f0;"|'''Data, Methods & Implementation  Challenges'''
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| align="center" style="background:#f0f0f0;"|'''Effective Nursing, Biomedical, and Health Sciences Approaches'''
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| Lack of access to existing, effective, modern, active-learning resources || Embrace Open and FAIR Data Science
 
| Lack of access to existing, effective, modern, active-learning resources || Embrace Open and FAIR Data Science

Revision as of 12:26, 13 April 2022

== SOCR News & Events: Leadership, Analytics and Innovation (LAI) Master’s Program 4-Day Intensive (May 17, 2022)

==
LAI 4DayIntensive 2022.jpg

Logistics

Challenges

Data, Methods & Implementation Challenges Effective Nursing, Biomedical, and Health Sciences Approaches
Lack of access to existing, effective, modern, active-learning resources Embrace Open and FAIR Data Science
Credit, acknowledgement, and recognition Give credit, entice independent enhancements
Storage, computing, networking limitations Challenging, but Google, MS, AMZ, NVIDIA, RStudio provide free Ed support
Collaboration Engage with fellow academics (e.g., MBDH, professional Societies), offer open-enrollment in short courses, MOOCs, other electives, Collaborate with partners on R&D projects
Cross-institutional partnerships (limited time, funding, HR),
Transdisciplinary interactions (non-trivial), Collaborate with partners on R&D projects
Application domain repurposing (requires team-science support)
Decision science and implementation of ML/AI into clinical practice Use a team science approach, embedding nurses, clinicians, statisticians and engineers

Core Principles

  • Team Science approach to tackling difficult healthcare challenges (science, implementation, translation, costs, outcomes, equity)
  • FAIR (Findable, Accessible, Interoperable, and Reusable) resources
  • Supporting the common-good, equitable, fair, transparent, trustworthy, rigorous, transdisciplinary, and sustainable Leadership, Analytics & Innovation in Nursing & Healthcare

Demonstrations

Contact

Questions, comments, collaborations, and suggestions are always welcome.





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