Scientific Computing and Data / AIR·MS (AI Ready Mount Sinai) / AIR·MS and Minerva Acknowledgements
Cite and Acknowledge AIR·MS and Scientific Computing and Data (Minerva) Resources in Publications
Why?
Please both acknowledge and cite AIR·MS and Scientific Computing and Data (Minerva) resources in publications. Recognition of use of these resources is important for acquiring funding for our research and development activities in AI-driven healthcare.
How to Cite AIR·MS in your Publication
Please cite the AIR·MS platform and technologies adopted in all your publications using:
- Guerrero, P., Ernebjerg, M., Holst, T., et al. The AIR·MS data platform for artificial intelligence in healthcare. JAMIA Open, 2025;8(6):ooaf145. https://doi.org/10.1093/jamiaopen/ooaf145
How to Cite Minerva in your Publication
Please cite Minerva platform and the technologies adopted in all your publications using:
- Kovatch P., Gai L., Cho HM., Fluder E., Jiang D. Optimizing High-Performance Computing Systems for Biomedical Workloads. IEEE Int Symp Parallel Distrib Process Workshops Phd Forum. 2020 May;2020:183-192. doi: 10.1109/ipdpsw50202.2020.00040. Epub 2020 Jul 28. PMID: 33088611; PMCID: PMC7575271
How to Acknowledge Funding Sources
All publications utilizing AIR·MS and Scientific Computing and Data (Minerva) resources must include the following acknowledgement:
- AIR·MS: This work is supported in part through the use of the research platform AI-Ready Mount Sinai (AIR·MS) and the expertise provided by the team at the Hasso Plattner Institute for Digital Health at Mount Sinai (HPI·MS).
- Minerva: This work is supported in part through the Minerva computational and data resources and staff expertise provided by Scientific Computing and Data at the Icahn School of Medicine at Mount Sinai and supported by the Clinical and Translational Science Awards (CTSA) grant UL1TR004419 from the National Center for Advancing Translational Sciences.