Mining of clinical and biomedical text and data: Editorial of the special issue

To cope with the amounts of documentation in health care and bio-medical research, the traditional intermediaries used by practitioners include, for example, summaries, code lists, and rulebooks. The new intermediaries enabled by text and data mining may encompass, for example, code suggestions assigned by text classification tools, rankings produced by information retrieval tools, pre-completed forms filled by information extraction tools, as well as structured free-text notes generated by topic segmentation and labelling tools. Under time constraints, they can help focus on essential items in large sets of data and text. This Special Issue is about these intermediaries.