Data Science in Anesthesiology and Intensive Care

Anesthesiology and Intensive Care are fields in medicine that have long collected data systematically. In the last years, new statistical techniques and increased availability of high-performance hardware, including but not limited to machine learning, have emerged that facilitate the analysis of large data-sets. So far, the majority of research in this field has been done on one publicly available dataset, the MIMIC-database.

This Research Topic aims to discover:

- What are the current approaches to collect, handle, harmonize and analyze medical data?

- What Language Models are used?

- What tools are used?

- Who works with on-site collected data? Who works solely with external datasets, e.g. MIMIC?

- Which sites have a federated analysis network in place? Who is involved?

- If and when yes how are insights gained by monitoring already integrated in the clinical workflow?

We are interested in a) the current approaches to handling large amounts of medical data, especially anesthesiological and intensive care data derived from sensors and b) the insights already gained from the analysis of these large, locally acquired datasets.

This Research Topic accepts multiple forms of manuscript, from original research to systematic reviews.