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.