Laboratory Tests And Diagnostic Procedures Chernecky Pdf

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

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. Combining the three sources reached a recall of 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.

Lab tests are one of the principal sources of information for decision making in diagnosis of medical problems, determination of prognosis and monitoring disease progression. Linking lab tests with their associated diseases electronically could improve differential diagnosis of diseases 1 , enhance healthcare quality 2 , reduce adverse events and liability claims 3 and facilitate computational research applications e.

However, building a computable knowledge base containing comprehensive disease-lab test relations is not a trivial task and it requires substantial efforts. Current research on this topic is very limited. Although many knowledge bases or ontologies of diseases and lab tests exist, few of them containing disease-lab test relations.

For example, the Unified Medical Language System UMLS 5 is a comprehensive resources containing various types of biomedical concepts including diseases and lab tests; but explicit relations between diseases and lab tests in the Semantic Network of UMLS are limited.

Disease ontology 6 , as a comprehensive knowledge base of inherited, developmental and acquired human diseases, does not provide linkages to lab tests either. Expert systems such as Quick Medical Reference QMR 8 contain relations between diseases and lab tests, in order to support decisions of differential diagnosis. Nevertheless, maintenance of such knowledge mainly depends on domain experts, which is time consuming and costly. Furthermore, such knowledge is not freely available for publics.

Several studies have attempted to extract disease and lab test relations from biomedical literature or clinical data. Halil et al. Wright et al. Despite of some success of these initial efforts, challenges still exist for automatically extracting disease-lab test relations from these resources. First, lab test names are dynamic e. Second, the distribution of relations between diseases and lab tests could be skewed. For example, an analysis of EHR data by Wright and Bates 14 shows that lab tests exhibit a power law distribution, with the top 4.

Furthermore, no single sources even standard reference books could cover all lab tests and their associated diseases 11 ; therefore, it is necessary to develop approaches that can extract and compile disease-lab test relations from multiple existing resources. As emerging recently, many on-line publicly available resources provide rich medical information for both consumers and healthcare providers. Those resources have the potential to be leveraged for building clinical knowledge bases, which are attracting increasing research interests.

For example, Wei et al 15 used public resources including Wikipedia and MedlinePlus to extract drug and indication relations and achieved promising results. Jona et al. Their study suggested that Wikipedia is an accurate and comprehensive source of drug-related information for undergraduate medical education.

As an initial step towards building a comprehensive, computable knowledge base of disease and lab tests relations, this paper describes our efforts to integrate three on-line resources, LabTestsOnline, MedlinePlus and Wikipedia, to create a freely available, computable disease-lab test resource.

The aim of this study has two-fold: 1 to examine whether it is feasible to automatically extract disease-lab test relations from online healthcare information resources with high performance; and 2 to investigate the coverage of disease and lab tests relations of online resources, in comparison with a gold standard reference book. To extract relation of diseases and lab tests from the three on-line resources, relevant web pages of diseases and lab tests need to be retrieved first.

LabTestsOnline provides an index of web pages about lab tests. All the web pages are downloaded based on the index. The html formats of web pages retrieved from LabTestsOnline and Wikipedia were analyzed and stored in text files. We used MetaMap 16 to process the free-text of each resource to recognize diseases and lab tests and mapped them to UMLS concepts.

The disease concepts are restricted to certain semantic types in the UMLS semantic groups 17 such as disorder. If a disease concept and a lab test concept co-occurred in the same web page, they are treated as a candidate relation pair.

Furthermore, to enhance the precision, we further developed source-specific rules to add more constraints to relation extraction process, e. The processing of each resource is described below:. LabTestsOnline usually describes the usage of multiple related lab tests and the indications of test results in one lab test web page.

Hence, diseases occurred in this section are extracted and used to form pairs with the given lab test. Usually, each entry in these sections is one single named entity of lab test, symptom or therapy et al, which could be recognized by MetaMap straightforwardly.

An information box of Medical Encyclopedia with related entries about the disease is also included, most of which are lab tests. Therefore, relation pairs are formed between diseases recognized in the title or disease summary and lab tests in the Medical Encyclopedia section.

As a collaboratively edited open encyclopedia, the coverage of information provided in Wikipedia is unbalanced across different diseases. The sections in disease webpages are often more diverse, when compared with LabTestOnline and MedlinePlus.

The extracted disease lab test relations are evaluated using precision and recall, which are defined as follows: Precision , as calculated in Equation 1 , measures the percentage of correct relation pairs among all relations extracted by our systems from each source.

In this study, relation pairs were randomly chosen from each resource and were manually checked by reviewing the original text. Recall , as calculated in Equation 2 , measures the percentage of system-extracted relation pairs among all relations defined in the gold standard. Here we used the disease lab test relation pairs in the book Laboratory Tests and Diagnostic Procedures by Chernecky and Berger 17 as gold standard, which contains information on common laboratory test results and their uses.

To evaluate our approach, we created a subset of know disease-lab test relations from the above reference book, by randomly selecting five common diseases from common health topics in WebMD 2 : Alcohol dependence syndrome, Acute myocardial infarction, Congestive heart failure, Rheumatoid arthritis, and Urinary Tract Infection, as well as five rare diseases from the rare diseases list provided by the Office of Rare Disease Research of National Institute of Health 3 : Glucocorticoid deficiency, Multiple sclerosis, Malaria, Multiple myeloma, and Cystic fibrosis.

In total, relation pairs 64 for five common diseases and 48 for five rare diseases were selected as gold standard for measuring the recall of the system. In addition, we also compared overlaps among all disease-lab test relations extracted from each source.

Table 1 shows the precision of each resource using one hundred randomly chosen relations. In contrast, recalls displayed in Figure 1 shows the converse result. LabTestsOnline obtained the highest recall for both common diseases As illustrated in Figure 1 , the combination of all the three sources enhanced the recall sharply, with Figure 2 illustrates the total numbers of diseases, lab tests and relations extracted from each resource and their overlaps.

In total, 3, relation pairs consisting of diseases and lab tests were extracted from LabTestsOnline; relation pairs consisting of diseases and lab tests were extracted from MedlinePlus; 2, relation pairs consisting of diseases and lab tests were extracted from Wikipedia. Examination of overlap among the three sources showed that diseases, lab tests, and relations were extracted from at least two resources.

Linking diseases and associated lab tests is valuable for clinical care and a wide range of clinical applications. This study is an initial effort to build a computable knowledge base for disease and lab test relations by integrating three on-line resources.

Combining the three sources achieved a recall of Moreover, among the ten diseases we explored, the three on-line resources also contributed five disease-lab test relations that are not included in the gold standard, e. These findings indicate that it is feasible to extract disease-lab test relations from such online sources and more importantly, relations in the on-line resources, as well as the gold standard reference book are complementary to each other for building a comprehensive disease and lab test relation knowledge base.

Furthermore, our automatic method for relation extraction has advantages in terms of cost and time, as constantly updating an expert-curated knowledge base to account for new clinical knowledge is time consuming and costly. Based on our manual review, one of the major reasons for the false positive relations is the fact that the concept of disease or lab test is too general to make a clinically valuable relation.

For example, when relations between Heart Diseases and lab tests are extracted from MedlinePlus, Heart Diseases describe a broad range of conditions, such as coronary artery disease, arrhythmias and congenital heart defects, to name a few. The lab test should be linked to a specific disease, instead of general categories. Similarly, some tests are expressed in broader terms in some well-known clinical cases.

Blood smear required for malaria disease may just be referred as the general concept microscopy when mentioned later in the text, which in turn may not be properly traced back and encoded into the specific microscopic examination i.

This issue of granularity is also one of the major causes for the low relation overlap between different resources. The general concepts of diseases and lab tests should be expanded or filtered out of the relation sets in the continuing studies.

Mistakes in recognition of diseases and lab tests as appropriate named entities are another major cause for errors in both precision and recall. For instance, different sources use varying terminologies and prefer common language based on their target audiences.

However, MetaMap failed to recognize it. Improving the performance of disease and lab test recognition may lead to a better relation extraction performance. One limitation of this study is that currently the relations between diseases and lab tests are not defined in a fine granularity. A lab test could be used for differential diagnosis, prognosis, progress monitoring of a disease, etc. Our future plan is to refine the relation types in terms of the functional association of lab tests with the disease.

In the next stage, we also plan to expand resources for relation extraction, including existing reference books and clinical manual and textbooks for medical education. Furthermore, machine learning based methods will be exploited to improve the performance of relation extraction. In this study, three public on-line resources are integrated to create a freely available, computable disease-lab test resource using an automated text mining method.

Experimental results indicate that it is feasible to automatically extract disease-lab test relations from the three online resources, and such online knowledge sources, as well as the gold standard reference book are complementary to each other for building a comprehensive disease and lab test relation knowledge base.

National Center for Biotechnology Information , U. Author information Copyright and License information Disclaimer. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose.

Abstract A computable knowledge base containing relations between diseases and lab tests would be a great resource for many biomedical informatics applications.

Disease and lab test concept recognition We used MetaMap 16 to process the free-text of each resource to recognize diseases and lab tests and mapped them to UMLS concepts. Disease — lab test relation extraction If a disease concept and a lab test concept co-occurred in the same web page, they are treated as a candidate relation pair.

The processing of each resource is described below: LabTestsOnline LabTestsOnline usually describes the usage of multiple related lab tests and the indications of test results in one lab test web page.

Wikipedia As a collaboratively edited open encyclopedia, the coverage of information provided in Wikipedia is unbalanced across different diseases. Evaluation The extracted disease lab test relations are evaluated using precision and recall, which are defined as follows: Precision , as calculated in Equation 1 , measures the percentage of correct relation pairs among all relations extracted by our systems from each source. Results Table 1 shows the precision of each resource using one hundred randomly chosen relations.

Open in a separate window. Figure 1. Table 1. Figure 2.

Chernecky & Berger: Laboratory Tests and Diagnostic Procedures, 5th ed.

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. Combining the three sources reached a recall of 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.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy. See our Privacy Policy and User Agreement for details. Published on Aug 18, Pub Date: Jun Pages: in Publisher: Saunders Look no further for quick complete answers to questions such as which laboratory tests to order or what the results might mean Laboratory Tests And Diagnostic Procedures 5th Edition covers more tests than any other reference of its kind.

Laboratory Tests and Diagnostic Procedures - E-Book (eBook)

All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. As new research and experience broaden our knowledge, changes in practice, treatment and drug therapy may become necessary or appropriate. Readers are advised to check the most current information provided i on procedures featured or ii by the manufacturer of each product to be administered, to verify the recommended dose or formula, the method and duration of administration, and contraindications.

Find complete answers to questions such as which laboratory tests to order or what the results might mean. Laboratory Tests and Diagnostic Procedures, 6th Edition covers more tests than any other reference of its kind, with over lab tests and diagnostic procedures in all. In Part I, you'll find an alphabetical list of hundreds of diseases, conditions, and symptoms, including the tests and procedures most commonly used to confirm or rule out a suspected diagnosis. In Part II, you'll find descriptions of virtually every laboratory and diagnostic test available.

Laboratory Tests and Diagnostic Procedures / Edition 6

Cardiac Blood Pool Scan

Laboratory Tests and Diagnostic Procedures, 6th Edition covers more tests than any other reference of its kind, with over lab tests and. Numerous and frequently-updated resource results are available from this WorldCat. Please choose whether or not you want other users to be able to see on your profile that this library is a favorite of yours. Please select Ok if you would like to proceed with this request anyway. All rights reserved.

Find complete answers to questions such as which laboratory tests to order or what the results might mean. Laboratory Tests and Diagnostic Procedures, 6th Edition covers more tests than any other reference of its kind, with over lab tests and diagnostic procedures in all. In Part I, you'll find an alphabetical list of hundreds of diseases, conditions, and symptoms, including the tests and procedures most commonly used to confirm or rule out a suspected diagnosis. This edition is updated with the latest research and over 20 NEW test entries. We are always looking for ways to improve customer experience on Elsevier. We would like to ask you for a moment of your time to fill in a short questionnaire, at the end of your visit.

The medical information provided is for informational purposes only and is not to be used as a substitute for professional medical advice, diagnosis or treatment. Please contact your health care provider with questions you may have regarding medical conditions or the interpretation of test results. The basic metabolic panel is a group of blood tests that provides information about your body's metabolism. How the Test is Performed A blood sample is needed. Most of the time blood is drawn from a vein located on the inside of the elbow or the back of the hand. Normal value ranges may vary slightly among different laboratories.

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A cardiac blood pool scan shows how well your heart is pumping blood to the rest of your body. During this test, a small amount of a radioactive substance called a tracer is injected into a vein. A gamma camera detects the radioactive material as it flows through the heart and lungs. The percentage of blood pumped out of the heart with each heartbeat is called the ejection fraction. It provides an estimate of how well the heart is working. This test has other names, including cardiac flow study, cardiac nuclear scan, first-pass scan, and MUGA scan.

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Laboratory Tests and Diagnostic Procedures

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