Abstract: A method for generating a knowledge data model is provided. The method includes providing at least one initial set of semantic type entities of a specific semantic type. The initial set of semantic type entities is expanded using available mappings between entities of the initial set and entities of unspecified type to generate an extended set of semantic type entities. Entities of a same semantic type are clustered within the extended set of semantic type entities. The method maps semantic relations between entities of different semantic type to relations between corresponding clusters containing the entities to generate the knowledge data model.

Abstract: A system for extracting relations between measurements within an unstructured text and ontology concepts of at least one domain ontology stored in a domain ontology database is provided. The system includes an annotation unit adapted to process sentences of the unstructured text to derive tokens and measurements within the sentences. The derived tokens are annotated with ontology concepts mapped to the tokens. The system also includes a concept analyzing unit adapted to analyze, for each annotated sentence including at least one derived measurement, the annotated ontology concepts mapped to the derived tokens of the sentence to identify the ontology concepts related to the at least one derived measurement and to rank the identified related ontology concepts according to calculated relation strengths of the relations between the identified related ontology concepts and the respective measurement of the annotated sentence.

Abstract: A method and system for supporting a clinical diagnosis is provided, the method including the steps of representing a patient by a plurality of initial symptoms, the symptoms including characteristics of the patient; determining, by querying and reasoning in a disease-symptom knowledge model, at least one likely disease for each of the plurality of initial symptoms; mapping the plurality of initial symptoms onto a set of said likely diseases; determining for each disease of said set of likely diseases a plurality of associated symptoms, the associated symptoms being associated to a respective disease of said set of likely diseases in said disease-symptom knowledge model; categorizing each of the plurality of associated symptoms into disjoint categories by mapping associated symptoms with initial symptoms; and representing likely diseases in the context of said categories of associated symptoms.

Abstract: Concept labels of an ontology are extended. An ontology includes concepts at least partially authored in a source language; a corpus at least partially authored in a target language is provided; said corpus is processed by a linguistical analysis and receiving a list of first terms as a result of said linguistical analysis, said first terms in said list ordered by a linguistical relevancy; within said list, at least one of said first terms is associated with an associated second term, said second term being a translation of said first term into said source language; a retrieval is conducted by using at least one of said second terms for identifying a matching concept within said ontology; and a concept label of said matching concept is extended by a first term associated to said second term of a matching retrieval.

Abstract: A method of composing an integrated ontology is provided. The method makes use of feature models for the process of modular development of ontologies. The feature models are adapted to assist the user in the process of selection of appropriate and combinable ontologies from an ontology repository for a given use case scenario. The usage of a feature model provides a view of all possible combinations, i.e. all combinations that do not result in an inconsistent ontology. The feature model is specifying dependencies between different ontologies thereby expediting the selection of appropriate ontologies. The usage of reasoning techniques provides for an in-situ consideration of restrictions for the selection of ontologies.

Abstract: Methods and systems may support conclusions of a clinician by enabling the clinician to arbitrarily define the symptoms according to the patient's record. The method may comprise: (a) determining a plurality of symptoms representing a patient and including characteristics of the patient, the symptoms being categorized as present symptoms, absent symptoms or open symptoms; (b) establishing a multi-tier relationship between said symptoms and a plurality of diseases based on a knowledge model; (c) adjusting weighting factor(s) for at least one multi-tier relationship based on said knowledge model; (d) optionally adjusting at least one weighting factor of step (c) by an expert; and (e) building a ranking of diseases from said multi-tier relationship based on said weighting factors. The method may provide an efficient ranking of disease information, thereby supporting a clinical diagnosis that may consider multiple symptoms while emphasizing particular symptoms in view of the clinician's expertise.

Abstract: A method and system for supporting a clinical diagnosis is provided, the method including the steps of representing a patient by a plurality of initial symptoms, the symptoms including characteristics of the patient; determining, by querying and reasoning in a disease-symptom knowledge model, at least one likely disease for each of the plurality of initial symptoms; mapping the plurality of initial symptoms onto a set of said likely diseases; determining for each disease of said set of likely diseases a plurality of associated symptoms, the associated symptoms being associated to a respective disease of said set of likely diseases in said disease-symptom knowledge model; categorizing each of the plurality of associated symptoms into disjoint categories by mapping associated symptoms with initial symptoms; and representing likely diseases in the context of said categories of associated symptoms.

Abstract: Methods and systems may support conclusions of a clinician by enabling the clinician to arbitrarily define the symptoms according to the patient's record. The method may comprise: (a) determining a plurality of symptoms representing a patient and including characteristics of the patient, the symptoms being categorized as present symptoms, absent symptoms or open symptoms; (b) establishing a multi-tier relationship between said symptoms and a plurality of diseases based on a knowledge model; (c) adjusting weighting factor(s) for at least one multi-tier relationship based on said knowledge model; (d) optionally adjusting at least one weighting factor of step (c) by an expert; and (e) building a ranking of diseases from said multi-tier relationship based on said weighting factors. The method may provide an efficient ranking of disease information, thereby supporting a clinical diagnosis that may consider multiple symptoms while emphasizing particular symptoms in view of the clinician's expertise.