SoN LAI 4 Day Intensive May 2022
== SOCR News & Events: Leadership, Analytics and Innovation (LAI) Master’s Program 4-Day Intensive (May 17, 2022)
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Logistics
- Event Date/Time: May 17, 2022, 1:00-1:30 PM (US Eastern Time)
- Location: LAI Program 4-Day Intensive, SNB Building, University of Michigan.
- Format: Residential/In-person
- RSVP (required): RSVP
- Ivo Dinov's Presentation LAI in Data-Driven, Evidence-based, and Technology-Enhanced Health Science.
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
- Resource navigators (graphical, key phrase search)
- Electronic books - Data Science and Predictive Analytics (DSPA) active-learning resources, Scientific Methods for Health Sciences, Probability and Statistics EBook
- Case-studies and driving motivational challenges, open data resources
- Webapps - Motion Charts, Pressure Injury Prediction Model, UK Biobank, SOCR Analytical Toolbox
- Collaborative Open-Science (Ongoing Research Project, Consulting, Pubs).
Contact
Questions, comments, collaborations, and suggestions are always welcome.
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