Jonathan Mortensen

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With increasing adoption of electronic health records (EHRs), there is an opportunity to use the free-text portion of EHRs for pharmacovigilance. We present novel methods that annotate the unstructured clinical notes and transform them into a deidentified patient-feature matrix encoded using medical terminologies. We demonstrate the use of the resulting(More)
Ontology evaluation has proven to be one of the more difficult problems in ontology engineering. Researchers proposed numerous methods to evaluate logical correctness of an ontology, its structure, or coverage of a domain represented by a corpus. However, evaluating whether or not ontology assertions correspond to the real world remains a manual and(More)
In recent years there has been a large amount of research into capturing, publishing and analysing Ontology Design Patterns (ODPs). However, there has not been any analysis into the typical language expressivity required to represent ODPs and how these requirements sit with lightweight fragments of the widely used ontology language OWL. In this paper we(More)
Although countless highly penetrant variants have been associated with Mendelian disorders, the genetic etiologies underlying complex diseases remain largely unresolved. By mining the medical records of over 110 million patients, we examine the extent to which Mendelian variation contributes to complex disease risk. We detect thousands of associations(More)
Biomedical ontologies are often large and complex, making ontology development and maintenance a challenge. To address this challenge, scientists use automated techniques to alleviate the difficulty of ontology development. However, for many ontology-engineering tasks, human judgment is still necessary. Microtask crowdsourcing, wherein human workers receive(More)
Biomedical ontologies are becoming increasingly large and complex. A single user cannot easily develop or maintain them. Researchers have developed various automated techniques to assist with ontology development and engineering at scale. However, these solutions are not always complete. Microtask crowdsourcing, wherein workers are paid small amounts to(More)
OBJECTIVES The verification of biomedical ontologies is an arduous process that typically involves peer review by subject-matter experts. This work evaluated the ability of crowdsourcing methods to detect errors in SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) and to address the challenges of scalable ontology verification. METHODS We(More)
It is increasingly evident that the realization of the Semantic Web will require not only computation, but also human contribution. Crowdsourcing is becoming a popular method to inject this human element. Researchers have shown how crowdsourcing can contribute to managing semantic data. One particular area that requires significant human curation is(More)