EHealth Syntactic and Semantic Analysis Features

• Clinical documents and documentation guidelines:
  • their content and language analysis (e.g., syntax, semantics, discourse, dialogue, pragmatics and word sense disambiguation);
  • their use in personalized medicine, healthcare work-flow, clinical trials as well as science and related information systems; and
  • their collaborative exchange between provider and patient, between providers in different organizations, or between different professions and the related topics of computer-supported cooperative work and human-computer interaction;
  • language generation for interactive and dialogue-based documentation and text production;

• (semi-)automated re-use of text content:
  • decision support (e.g., reasoning and meta-reasoning);
  • identification and removal of privacy-sensitive and identifying information;
  • IE;
  • information visualization;
  • IR;
  • machine translation;
  • referent tracking and management;
  • sentiment analysis;
  • text classification;
  • text clustering;
  • text summarization;
  • textual entailment and paraphrasing;
  • TM; and
  • topic analysis;

• Knowledge acquisition:
  • analysis and integration of eHealth documents across languages, genres and jargons;
  • combining documents from multiple sources; and – combinations of text and encoded/structured information; annotation and evaluation:
  • annotated health resources and science of annotation;
  • dictionaries, ontologies, standards and other linguistic resources;
  • evaluation metrics, methods, protocols and infrastructure; and
  • evaluation results and protocols across care settings, organizations and languages.