The description logic EL has recently proved practically useful in the life science domain with presence of several large-scale biomedical ontologies such as Snomed ct. To deal with ontologies of this scale, standard reasoning of classification is essential but not sufficient. The ability to extract relevant fragments from a large ontology and to incrementally classify it has become more crucia...

We have developed a program for extracting the diagnoses and procedures from the past medical history and discharge diagnoses in the discharge summary of a case and coding these using SNOMED-CT in the UMLS. The program uses a limited amount of natural language processing. Rather, it makes use of the relatively standard structure of the discharge summary, a small dictionary to divide the text in...

A descriptive study of health information technology (HIT) vendors was conducted to identify which EMR/EHR vendors currently work or anticipate working with SNOMED CT, determine the prevalence of SNOMED CT integration in electronic medical record (EMR) and electronic health record (EHR) products, identify the available and potential future applications for SNOMED CT in EMR/EHR systems, and lear...

Comparative biological studies have led to remarkable biomedical discoveries. While genomic science and technologies are advancing rapidly, our ability to precisely specify a phenotype and compare it to related phenotypes of other organisms remains challenging. This study has examined the systematic use of terminology and knowledge based technologies to enable high-throughput comparative phenom...

An algorithm was derived to find candidate mappings between any two terminologies inside the UMLS, making use of synonymy, explicit mapping relations and hierarchical relationships among UMLS concepts. Using an existing set of mappings from SNOMED CT to ICD9CM as our gold standard, we managed to find candidate mappings for 86% of SNOMED CT terms, with recall of 42% and precision of 20%. Among t...

Semantic-similarity measures quantify concept similarities in a given ontology. Potential applications for these measures include search, data mining, and knowledge discovery in database or decision-support systems that utilize ontologies. To date, there have not been comparisons of the different semantic-similarity approaches on a single ontology. Such a comparison can offer insight on the val...

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 remuneration to complete simple, shor...

Modern medical vocabularies can contain up to hundreds of thousands of terms. In any particular use-case only a small fraction of these will be needed. In this paper we first define two notions of a diseasecentric subdomain of a large ontology. We then explore two methods for identifying disease-centric subdomains of such large medical vocabularies. The first method is based on lexically queryi...

Motivation: Our goal is first to create a biomedical ontology relating diseases and pathways, and second to exploit this knowledge. We first created a knowledge source relating diseases and pathways by integrating GO, KEGG orthology and SNOMED CT. We proposed an approach combining mapping and alignment techniques. We used OWL-DL as the common representation formalism. Second, we demonstrated th...

OBJECTIVE To develop and evaluate machine learning techniques that identify limb fractures and other abnormalities (e.g. dislocations) from radiology reports. MATERIALS AND METHODS 99 free-text reports of limb radiology examinations were acquired from an Australian public hospital. Two clinicians were employed to identify fractures and abnormalities from the reports; a third senior clinician ...