AI Resource Hub for Healthcare Research
Recently, we co-developed a framework for advanced analytics in healthcare research infrastructure in collaboration with the Australian Data Science Network. This framework, co-created through an extensive co-design process involving environmental scans, interviews, surveys, and workshops, provides comprehensive guidance by capturing the needs and aspirations of researchers. Participants highlighted challenges, concerns, and opportunities across all stages of the advanced analytics lifecycle, including the need for socio-technical infrastructure. This includes training resources, governance structures, guidelines, communities of practice (CoPs), and facilitation support. While there are numerous courses and a handful of practice guidelines in existence, context specific knowledge, imparted in a user-friendly fashion, is in short supply. In an upcoming initiative, we aim to collaborate with research and pedagogical practitioners to co-develop and deliver relevant socio-technical assets as co-investment projects. These outputs will be embedded into virtual labs and resource hubs through engaging tools such as AI co-pilots and intelligent tutors. We invite the community to join us in this effort, whether through creating new contents, assessing or augmenting existing contents, or through designing and developing delivery vehicles via innovative platforms like chatbots or co-pilots. The resulting open-source materials could also be reused in your class rooms.
Institutions
- Australian Research Data Commons (AU)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-12-02
- DOI
- https://doi.org/10.5281/zenodo.14257195
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00