Extracting Patient Case Profiles with Domain-Specific Semantic Categories

Extracting Patient Case Profiles with Domain-Specific Semantic Categories

Yitao Zhang (The University of Sydney, Australia) and Jon Patrick (The University of Sydney, Australia)
DOI: 10.4018/978-1-60566-274-9.ch014
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Abstract

The fast growing content of online articles of clinical case studies provides a useful source for extracting domain-specific knowledge for improving healthcare systems. However, current studies are more focused on the abstract of a published case study which contains little information about the detailed case profiles of a patient, such as symptoms and signs, and important laboratory test results of the patient from the diagnostic and treatment procedures. This paper proposes a novel category set to cover a wide variety of semantics in the description of clinical case studies which distinguishes each unique patient case. A manually annotated corpus consisting of over 5000 sentences from 75 journal articles of clinical case studies has been created. A sentence classification system which identifies 13 classes of clinically relevant content has been developed. A golden standard for assessing the automatic classifications has been established by manual annotation. A maximum entropy (MaxEnt) classifier is shown to produce better results than a Support Vector Machine (SVM) classifier on the corpus.
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Introduction

The medical diagnosis and treatment of a patient is a complex procedure which requires relevant knowledge and clinical experience of illnesses. In order to distinguish different illnesses that show similar signs and symptoms, or to decide the best available option for treatment of a medical condition, physicians need to have adequate observations of similar patient cases, either from their own previous medical practices, or some external resources, such as the knowledge of more experienced colleagues, and the medical literature on the latest progress in the field.

Clinical case reporting therefore plays an important role in both educating young physicians in the practice of medicine, and sharing clinical experience and exceptional findings among physicians (Jenicek, M., 2001). There are two types of clinical case reports, namely routine patient case reports and clinical case studies. Routine case reports are raw patient records of the diagnostic and treatment procedure and provide information which is necessary for the continuity of patient care, such as progress notes, discharge summaries and pathology reports. Clinical case studies, on the other hand, report rare and abnormal patient cases that are considered as of significant scientific value to the field. They are reported by clinicians, usually in the form of formal journal articles in medical press.

Narrative patient records produced by nurses and physicians everyday in hospitals and clinics, provide first-hand the richest information about the progress of patients. However, the confidentiality of personal records has always been a concern which prevents the research community having access to enough data to develop useful learning systems comparable to human performance. Confidential information includes names of patients and physicians, dates, and geographic clues which are required to be anonymized before any raw patient data can be released to the public. Moreover, the anonymisation task often requires human annotators to manually check every single patient record to satisfy certain laws and ethical guidelines specified by governments. For instance, the 2007 Computational Medicine Challenge had to use human annotators to review all of the 4,055 raw patient records and to remove nearly half of them from the final gold-standard corpus to meet United States HIPAA standards.

With the emergence of publicly available on-line knowledge bases such as MEDLINE/PubMed and BMC Central, clinicians now have access to a large number of full-text journal articles of clinical case studies. Each case study records a detailed discussion of the patient’s abnormal signs and symptoms, or novel conditions which are considered as report-worthy. While all the sensitive privacy information has been carefully removed from the text, a clinical case study still contains rich information about patient case profiles, such as patient demographics, signs and symptoms, laboratory test readings and interpretations, and treatments and subsequent outcomes for patients. This patient profile information is key in answering two fundamental questions dominating the daily practice of physicians: (1) Given the case profile of a patient, what is the best explanation or diagnosis of the condition? (2) Given the specified circumstances of a patient, what is the best treatment available? By exploring clinical case studies with similar patient profiles, physicians can learn, and therefore improve their practices of medicine, from the successes or failures of their peers.

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Table of Contents
Preface
Violaine Prince, Mathieu Roche
Chapter 1
Sophia Ananiadou
Text mining provides the automated means to manage information overload and overlook. By adding meaning to text, text mining techniques produce a... Sample PDF
Text Mining for Biomedicine
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Chapter 2
Dimitrios Kokkinakis
The identification and mapping of terminology from large repositories of life science data onto concept hierarchies constitute an important initial... Sample PDF
Lexical Granularity for Automatic Indexing and Means to Achieve It: The Case of Swedish MeSH®
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Chapter 3
M. Teresa Martín-Valdivia, Arturo Montejo-Ráez, M. C. Díaz-Galiano, José M. Perea Ortega, L. Alfonso Ureña-López
This chapter argues for the integration of clinical knowledge extracted from medical ontologies in order to improve a Multi-Label Text... Sample PDF
Expanding Terms with Medical Ontologies to Improve a Multi-Label Text Categorization System
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Chapter 4
Piotr Pezik, Antonio Jimeno Yepes, Dietrich Rebholz-Schuhmann
The present chapter discusses the use of terminological resources for Information Retrieval in the biomedical domain. The authors first introduce a... Sample PDF
Using Biomedical Terminological Resources for Information Retrieval
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Chapter 5
Laura Diosan, Alexandrina Rogozan, Jean-Pierre Pécuchet
The automatic alignment between a specialized terminology used by librarians in order to index concepts and a general vocabulary employed by a... Sample PDF
Automatic Alignment of Medical Terminologies with General Dictionaries for an Efficient Information Retrieval
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Chapter 6
Vincent Claveau
This chapter presents a simple yet efficient approach to translate automatically unknown biomedical terms from one language into another. This... Sample PDF
Translation of Biomedical Terms by Inferring Rewriting Rules
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Chapter 7
Nils Reiter, Paul Buitelaar
This chapter is concerned with lexical enrichment of ontologies, that is how to enrich a given ontology with lexical information derived from a... Sample PDF
Lexical Enrichment of Biomedical Ontologies
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Chapter 8
Torsten Schiemann, Ulf Leser, Jörg Hakenberg
Ambiguity is a common phenomenon in text, especially in the biomedical domain. For instance, it is frequently the case that a gene, a protein... Sample PDF
Word Sense Disambiguation in Biomedical Applications: A Machine Learning Approach
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Chapter 9
M. Narayanaswamy, K. E. Ravikumar, Z. Z. Hu, K. Vijay-Shanker, C. H. Wu
Protein posttranslational modification (PTM) is a fundamental biological process, and currently few text mining systems focus on PTM information... Sample PDF
Information Extraction of Protein Phosphorylation from Biomedical Literature
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Chapter 10
Yves Kodratoff, Jérôme Azé, Lise Fontaine
This chapter argues that in order to extract significant knowledge from masses of technical texts, it is necessary to provide the field specialists... Sample PDF
CorTag: A Language for a Contextual Tagging of the Words Within Their Sentence
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Chapter 11
Yun Niu, Graeme Hirst
The task of question answering (QA) is to find an accurate and precise answer to a natural language question in some predefined text. Most existing... Sample PDF
Analyzing the Text of Clinical Literature for Question Answering
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Chapter 12
Nadine Lucas
This chapter presents the challenge of integrating knowledge at higher levels of discourse than the sentence, to avoid “missing the forest for the... Sample PDF
Discourse Processing for Text Mining
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Chapter 13
Dimosthenis Kyriazis, Anastasios Doulamis, Theodora Varvarigou
In this chapter, a non-linear relevance feedback mechanism is proposed for increasing the performance and the reliability of information (medical... Sample PDF
A Neural Network Approach Implementing Non-Linear Relevance Feedback to Improve the Performance of Medical Information Retrieval Systems
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Chapter 14
Yitao Zhang, Jon Patrick
The fast growing content of online articles of clinical case studies provides a useful source for extracting domain-specific knowledge for improving... Sample PDF
Extracting Patient Case Profiles with Domain-Specific Semantic Categories
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Chapter 15
Laura I. Furlong, Ferran Sanz
SNPs constitute key elements in genetic epidemiology and pharmacogenomics. While data about genetic variation is found at sequence databases... Sample PDF
Identification of Sequence Variants of Genes from Biomedical Literature: The OSIRIS Approach
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Chapter 16
Francisco M. Couto, Mário J. Silva, Vivian Lee, Emily Dimmer, Evelyn Camon, Rolf Apweiler
Molecular Biology research projects produced vast amounts of data, part of which has been preserved in a variety of public databases. However, a... Sample PDF
Verification of Uncurated Protein Annotations
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Chapter 17
Burr Settles
ABNER (A Biomedical Named Entity Recognizer) is an open-source software tool for text mining in the molecular biology literature. It processes... Sample PDF
A Software Tool for Biomedical Information Extraction (And Beyond)
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Chapter 18
Asanee Kawtrakul, Chaveevarn Pechsiri, Sachit Rajbhandari, Frederic Andres
Valuable knowledge has been distributed in heterogeneous formats on many different Web sites and other sources over the Internet. However, finding... Sample PDF
Problems-Solving Map Extraction with Collective Intelligence Analysis and Language Engineering
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Chapter 19
Christophe Jouis, Magali Roux-Rouquié, Jean-Gabriel Ganascia
Identical molecules could play different roles depending of the relations they may have with different partners embedded in different processes, at... Sample PDF
Seekbio: Retrieval of Spatial Relations for System Biology
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Chapter 20
Jon Patrick, Pooyan Asgari
There have been few studies of large corpora of narrative notes collected from the health clinicians working at the point of care. This chapter... Sample PDF
Analysing Clinical Notes for Translation Research: Back to the Future
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About the Contributors