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Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction.

Zhang Y, Soysal E, Moon S, Wang J, Tao C, Xu H - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase.Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%.Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.

ABSTRACT
A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

No MeSH data available.


Related in: MedlinePlus

Recall of LabTestsOnline, MedlinePlus and Wikipedia and their combination for common and rare diseases.
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Related In: Results  -  Collection


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f1-2094611: Recall of LabTestsOnline, MedlinePlus and Wikipedia and their combination for common and rare diseases.

Mentions: Table 1 shows the precision of each resource using one hundred randomly chosen relations. Wikipedia had the highest precision of 87%, while LabTestsOnline demonstrated a lowest precision of 76%. In contrast, recalls (displayed in Figure 1) shows the converse result. LabTestsOnline obtained the highest recall for both common diseases (38.10%) and rare diseases (34.09%). and Wikipedia was the lowest, with 23.81% for the common disease and 22.73% for the rare disease. The precision (81%) and recall (common disease 26.98%; rare disease 25%) of MedlinePlus were in the middle of the other two resources. As illustrated in Figure 1, the combination of all the three sources enhanced the recall sharply, with 57.14% for the common disease and 45.45% for the rare diseases, demonstrating that the relations of the three sources are complementary to each other.


Integrating Multiple On-line Knowledge Bases for Disease-Lab Test Relation Extraction.

Zhang Y, Soysal E, Moon S, Wang J, Tao C, Xu H - AMIA Jt Summits Transl Sci Proc (2015)

Recall of LabTestsOnline, MedlinePlus and Wikipedia and their combination for common and rare diseases.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525275&req=5

f1-2094611: Recall of LabTestsOnline, MedlinePlus and Wikipedia and their combination for common and rare diseases.
Mentions: Table 1 shows the precision of each resource using one hundred randomly chosen relations. Wikipedia had the highest precision of 87%, while LabTestsOnline demonstrated a lowest precision of 76%. In contrast, recalls (displayed in Figure 1) shows the converse result. LabTestsOnline obtained the highest recall for both common diseases (38.10%) and rare diseases (34.09%). and Wikipedia was the lowest, with 23.81% for the common disease and 22.73% for the rare disease. The precision (81%) and recall (common disease 26.98%; rare disease 25%) of MedlinePlus were in the middle of the other two resources. As illustrated in Figure 1, the combination of all the three sources enhanced the recall sharply, with 57.14% for the common disease and 45.45% for the rare diseases, demonstrating that the relations of the three sources are complementary to each other.

Bottom Line: LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase.Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%.Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.

ABSTRACT
A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications. This paper describes our initial step towards establishing a comprehensive knowledge base of disease and lab tests relations utilizing three public on-line resources. LabTestsOnline, MedlinePlus and Wikipedia are integrated to create a freely available, computable disease-lab test knowledgebase. Disease and lab test concepts are identified using MetaMap and relations between diseases and lab tests are determined based on source-specific rules. Experimental results demonstrate a high precision for relation extraction, with Wikipedia achieving the highest precision of 87%. Combining the three sources reached a recall of 51.40%, when compared with a subset of disease-lab test relations extracted from a reference book. Moreover, we found additional disease-lab test relations from on-line resources, indicating they are complementary to existing reference books for building a comprehensive disease and lab test relation knowledge base.

No MeSH data available.


Related in: MedlinePlus