DrNote: An open medical annotation service.
Johann FreiIñaki Soto-ReyFrank KramerPublished in: PLOS digital health (2022)
In the context of clinical trials and medical research medical text mining can provide broader insights for various research scenarios by tapping additional text data sources and extracting relevant information that is often exclusively present in unstructured fashion. Although various works for data like electronic health reports are available for English texts, only limited work on tools for non-English text resources has been published that offers immediate practicality in terms of flexibility and initial setup. We introduce DrNote, an open source text annotation service for medical text processing. Our work provides an entire annotation pipeline with its focus on a fast yet effective and easy to use software implementation. Further, the software allows its users to define a custom annotation scope by filtering only for relevant entities that should be included in its knowledge base. The approach is based on OpenTapioca and combines the publicly available datasets from WikiData and Wikipedia, and thus, performs entity linking tasks. In contrast to other related work our service can easily be built upon any language-specific Wikipedia dataset in order to be trained on a specific target language. We provide a public demo instance of our DrNote annotation service at https://drnote.misit-augsburg.de/.
Keyphrases
- healthcare
- mental health
- smoking cessation
- rna seq
- clinical trial
- autism spectrum disorder
- electronic health record
- climate change
- big data
- data analysis
- primary care
- magnetic resonance
- emergency department
- single cell
- working memory
- public health
- computed tomography
- drinking water
- randomized controlled trial
- study protocol
- machine learning
- quality improvement
- risk assessment