• The CARESSES Ontology encodes guidelines defined by experts in Transcultural Nursing, with the aim of offering a specific tool for endowing social assistive robots (assisting older adults) with cultural competence. @en
  • The Cochrane Core ontology describes the entities and concepts that exist in the domain of evidence based healthcare. It is used for the construction of the Cochrane Linked Data Vocabulary containing some 400k terms including Interventions (Drugs, Procedures etc), Populations (Age, Sex, Condition), and clinical Outcomes. @en
  • An ontology for the Drug Bureau of Macedonia (DBM). @en
  • The ontology has been developed in the framework of the Dem@Care project for representing the experimentation protocol towards diagnostic support and assessment of Dementia in a controlled environment. The aim of the protocol is to provide a brief overview of their health status of the participants during consultation (cognition, behaviours and function), and to correlate the system (sensor) data with the data collected using typical dementia care assessment tools. @en
  • Ontology for healthcare metadata - especially metadata found in DICOM files (Digital Imaging and Communications in Medicine, see http://dicom.nema.org/). Author: Michael Brunnbauer, Bonubase GmbH (www.bonubase.com). The author's email address is brunni@netestate.de. See http://purl.org/healthcarevocab/v1help for explanations. @en
  • The Diabetes Pharmacology Ontology contains the classes needed to describe antihyperglycemic therapies. @en
  • An ontology for describing brand-name drugs. @en
  • A RDF Schema that defines concepts and relationships used for Hospital data. @en
  • This ontology aims to model generic Medical Data Acquisition Instruments, which can be interoperable across different clinical data management systems. The ontology is developed in the context of the MedRed project (https://www.hevs.ch/en/rad-institutes/institute-of-information-systems/projects/medical-research-data-acquisition-platform-14092) @en
  • The Ontology for Biomedical Investigations (OBI) is build in a collaborative, international effort and will serve as a resource for annotating biomedical investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. This ontology arose from the Functional Genomics Investigation Ontology (FuGO) and will contain both terms that are common to all biomedical investigations, including functional genomics investigations and those that are more domain specific. @en
  • The PICO ontology provides a machine accessible version of the PICO framework. It essentially provides a model for describing evidence in a consistent way. The model allows the specifying of complex populations, detailed interventions and their comparisons as well as the outcomes considered. The PICO ontology was originally designed to model the questions asked and answered in Cochrane's systematic reviews. As a leader in the field of evidence based healthcare Cochrane uses the PICO model when framing and publishing evidence based questions. The PICO model is widely adopted for describing healthcare evidence, furthermore is equally applicable in other evidence-based domains. It essentially provides a model for describing evidence in a consistent way. @en
  • The Translational Medicine Ontology (TMO) is a high-level, patient-centric ontology that extends existing domain ontologies to integrate data across aspects of drug discovery and clinical practice. The ontology has been developed by participants in the World Wide Web Consortium's Semantic Web for Health Care and Life Sciences Interest Group @en
  • Yoga Ontology is the list of vocabularies that define the yogic practice. Where Yoga is the union of the mind and body. @en