Text mining of web-based medical content:
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
[Place of publication not identified]
E-Content Generic Vendor
2014
|
| Schriftenreihe: | Speech Technology and Text Mining in Medicine and Health Care
|
| Schlagworte: | |
| Online-Zugang: | FAW01 FAW02 |
| Beschreibung: | Includes bibliographical references Preface; Contents; List of authors; Part I. Methods and techniques for mining biomedical literature and electronic health records; 1 Application of text mining to biomedical knowledge extraction: analyzing clinical narratives and medical literature; 1.1 Introduction; 1.2 Background; 1.2.1 Clinical and biomedical text; 1.2.2 Information retrieval; 1.2.2.1 Information retrieval process; 1.2.3 Information extraction; 1.2.4 Challenges to biomedical information extraction systems; 1.2.5 Applications of biomedical information extraction tools; 1.3 Biomedical knowledge extraction using text mining 1.3.1 Unstructured text gathering and preprocessing1.3.1.1 Text gathering; 1.3.1.2 Text preprocessing; 1.3.2 Extraction of features and semantic information; 1.3.3 Analysis of annotated texts; 1.3.3.1 Algorithms for text classification; 1.3.3.2 Classification evaluation measures; 1.3.4 Presentation; 1.4 Text mining tools; 1.5 Summary; Appendix "A"; References; 2 Unlocking information in electronic health records using natural language processing: a case study in medication information extraction; 2.1 Introduction to clinical natural language processing; 2.2 Medication information in EHRs 2.3 Medication information extraction systems and methods2.3.1 Relevant work; 2.3.2 Summary of approaches; 2.3.2.1 Rule-based methods; 2.3.2.2 Machine learning-based methods; 2.3.2.3 Hybrid methods; 2.4 Uses of medication information extraction tools in clinical research; 2.5 Challenges and future work; References; 3 Online health information semantic search and exploration: reporting on two prototypes for performing information extraction on both a hospital intranet and the world wide web; 3.1 Introduction; 3.2 Background; 3.3 Related work; 3.3.1 Semantic search 3.3.2 Health information search and exploration3.3.3 Information extraction for health; 3.3.4 Ontology-based information extraction -- OBIE; 3.4 A general architecture for health search: handling both private and public content; 3.5 Two semantic search systems for health; 3.5.1 MedInX; 3.5.1.1 MedInX ontologies; 3.5.1.2 MedInX system; 3.5.1.3 Representative results; 3.5.2 SPHInX -- Semantic search of public health information in Portuguese; 3.5.2.1 System architecture; 3.5.2.2 Natural language processing; 3.5.2.3 Semantic extraction models; 3.5.2.4 Semantic extraction and integration 3.5.2.5 Search and exploration3.6 Conclusion; Acknowledgments; References; Part II. Machine learning techniques for mining medical search queries and health-related social media posts and tweets; 4 Predicting dengue incidence in Thailand from online search queries that include weather and climatic variables; 4.1 Introduction; 4.1.1 Dengue disease in the world; 4.2 Epidemiology of dengue disease; 4.2.1 Temperature change and the ecology of A. aegypti; 4.3 Using online data to forecast incidence of dengue; 4.3.1 Background and related work; 4.3.2 Methodology for dengue cases prediction Text Mining of Web-Based Medical Content examines web mining for extracting useful information that can be used for treating and monitoring the healthcare of patients. This work provides methodological approaches to designing mapping tools that exploit data found in social media postings. Specific linguistic features of medical postings are analyzed vis-a-vis available data extraction tools for culling useful information |
| ISBN: | 1614513902 9781614513902 9781614515418 1614515417 9781614513919 1614513910 |
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| 500 | |a Preface; Contents; List of authors; Part I. Methods and techniques for mining biomedical literature and electronic health records; 1 Application of text mining to biomedical knowledge extraction: analyzing clinical narratives and medical literature; 1.1 Introduction; 1.2 Background; 1.2.1 Clinical and biomedical text; 1.2.2 Information retrieval; 1.2.2.1 Information retrieval process; 1.2.3 Information extraction; 1.2.4 Challenges to biomedical information extraction systems; 1.2.5 Applications of biomedical information extraction tools; 1.3 Biomedical knowledge extraction using text mining | ||
| 500 | |a 1.3.1 Unstructured text gathering and preprocessing1.3.1.1 Text gathering; 1.3.1.2 Text preprocessing; 1.3.2 Extraction of features and semantic information; 1.3.3 Analysis of annotated texts; 1.3.3.1 Algorithms for text classification; 1.3.3.2 Classification evaluation measures; 1.3.4 Presentation; 1.4 Text mining tools; 1.5 Summary; Appendix "A"; References; 2 Unlocking information in electronic health records using natural language processing: a case study in medication information extraction; 2.1 Introduction to clinical natural language processing; 2.2 Medication information in EHRs | ||
| 500 | |a 2.3 Medication information extraction systems and methods2.3.1 Relevant work; 2.3.2 Summary of approaches; 2.3.2.1 Rule-based methods; 2.3.2.2 Machine learning-based methods; 2.3.2.3 Hybrid methods; 2.4 Uses of medication information extraction tools in clinical research; 2.5 Challenges and future work; References; 3 Online health information semantic search and exploration: reporting on two prototypes for performing information extraction on both a hospital intranet and the world wide web; 3.1 Introduction; 3.2 Background; 3.3 Related work; 3.3.1 Semantic search | ||
| 500 | |a 3.3.2 Health information search and exploration3.3.3 Information extraction for health; 3.3.4 Ontology-based information extraction -- OBIE; 3.4 A general architecture for health search: handling both private and public content; 3.5 Two semantic search systems for health; 3.5.1 MedInX; 3.5.1.1 MedInX ontologies; 3.5.1.2 MedInX system; 3.5.1.3 Representative results; 3.5.2 SPHInX -- Semantic search of public health information in Portuguese; 3.5.2.1 System architecture; 3.5.2.2 Natural language processing; 3.5.2.3 Semantic extraction models; 3.5.2.4 Semantic extraction and integration | ||
| 500 | |a 3.5.2.5 Search and exploration3.6 Conclusion; Acknowledgments; References; Part II. Machine learning techniques for mining medical search queries and health-related social media posts and tweets; 4 Predicting dengue incidence in Thailand from online search queries that include weather and climatic variables; 4.1 Introduction; 4.1.1 Dengue disease in the world; 4.2 Epidemiology of dengue disease; 4.2.1 Temperature change and the ecology of A. aegypti; 4.3 Using online data to forecast incidence of dengue; 4.3.1 Background and related work; 4.3.2 Methodology for dengue cases prediction | ||
| 500 | |a Text Mining of Web-Based Medical Content examines web mining for extracting useful information that can be used for treating and monitoring the healthcare of patients. This work provides methodological approaches to designing mapping tools that exploit data found in social media postings. Specific linguistic features of medical postings are analyzed vis-a-vis available data extraction tools for culling useful information | ||
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| record_format | marc |
| series2 | Speech Technology and Text Mining in Medicine and Health Care |
| spelling | Text mining of web-based medical content [Place of publication not identified] E-Content Generic Vendor 2014 txt rdacontent c rdamedia cr rdacarrier Speech Technology and Text Mining in Medicine and Health Care Includes bibliographical references Preface; Contents; List of authors; Part I. Methods and techniques for mining biomedical literature and electronic health records; 1 Application of text mining to biomedical knowledge extraction: analyzing clinical narratives and medical literature; 1.1 Introduction; 1.2 Background; 1.2.1 Clinical and biomedical text; 1.2.2 Information retrieval; 1.2.2.1 Information retrieval process; 1.2.3 Information extraction; 1.2.4 Challenges to biomedical information extraction systems; 1.2.5 Applications of biomedical information extraction tools; 1.3 Biomedical knowledge extraction using text mining 1.3.1 Unstructured text gathering and preprocessing1.3.1.1 Text gathering; 1.3.1.2 Text preprocessing; 1.3.2 Extraction of features and semantic information; 1.3.3 Analysis of annotated texts; 1.3.3.1 Algorithms for text classification; 1.3.3.2 Classification evaluation measures; 1.3.4 Presentation; 1.4 Text mining tools; 1.5 Summary; Appendix "A"; References; 2 Unlocking information in electronic health records using natural language processing: a case study in medication information extraction; 2.1 Introduction to clinical natural language processing; 2.2 Medication information in EHRs 2.3 Medication information extraction systems and methods2.3.1 Relevant work; 2.3.2 Summary of approaches; 2.3.2.1 Rule-based methods; 2.3.2.2 Machine learning-based methods; 2.3.2.3 Hybrid methods; 2.4 Uses of medication information extraction tools in clinical research; 2.5 Challenges and future work; References; 3 Online health information semantic search and exploration: reporting on two prototypes for performing information extraction on both a hospital intranet and the world wide web; 3.1 Introduction; 3.2 Background; 3.3 Related work; 3.3.1 Semantic search 3.3.2 Health information search and exploration3.3.3 Information extraction for health; 3.3.4 Ontology-based information extraction -- OBIE; 3.4 A general architecture for health search: handling both private and public content; 3.5 Two semantic search systems for health; 3.5.1 MedInX; 3.5.1.1 MedInX ontologies; 3.5.1.2 MedInX system; 3.5.1.3 Representative results; 3.5.2 SPHInX -- Semantic search of public health information in Portuguese; 3.5.2.1 System architecture; 3.5.2.2 Natural language processing; 3.5.2.3 Semantic extraction models; 3.5.2.4 Semantic extraction and integration 3.5.2.5 Search and exploration3.6 Conclusion; Acknowledgments; References; Part II. Machine learning techniques for mining medical search queries and health-related social media posts and tweets; 4 Predicting dengue incidence in Thailand from online search queries that include weather and climatic variables; 4.1 Introduction; 4.1.1 Dengue disease in the world; 4.2 Epidemiology of dengue disease; 4.2.1 Temperature change and the ecology of A. aegypti; 4.3 Using online data to forecast incidence of dengue; 4.3.1 Background and related work; 4.3.2 Methodology for dengue cases prediction Text Mining of Web-Based Medical Content examines web mining for extracting useful information that can be used for treating and monitoring the healthcare of patients. This work provides methodological approaches to designing mapping tools that exploit data found in social media postings. Specific linguistic features of medical postings are analyzed vis-a-vis available data extraction tools for culling useful information HEALTH & FITNESS / Holism bisacsh HEALTH & FITNESS / Reference bisacsh MEDICAL / Alternative Medicine bisacsh MEDICAL / Atlases bisacsh MEDICAL / Essays bisacsh MEDICAL / Family & General Practice bisacsh MEDICAL / Holistic Medicine bisacsh MEDICAL / Osteopathy bisacsh Data mining fast Internet fast Medical informatics fast Medicine / Research fast Medizin Data mining Medicine Research Internet Medical informatics Medizinische Informatik (DE-588)4038261-8 gnd rswk-swf Text Mining (DE-588)4728093-1 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Medizinische Informatik (DE-588)4038261-8 s Text Mining (DE-588)4728093-1 s 2\p DE-604 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Text mining of web-based medical content HEALTH & FITNESS / Holism bisacsh HEALTH & FITNESS / Reference bisacsh MEDICAL / Alternative Medicine bisacsh MEDICAL / Atlases bisacsh MEDICAL / Essays bisacsh MEDICAL / Family & General Practice bisacsh MEDICAL / Holistic Medicine bisacsh MEDICAL / Osteopathy bisacsh Data mining fast Internet fast Medical informatics fast Medicine / Research fast Medizin Data mining Medicine Research Internet Medical informatics Medizinische Informatik (DE-588)4038261-8 gnd Text Mining (DE-588)4728093-1 gnd |
| subject_GND | (DE-588)4038261-8 (DE-588)4728093-1 (DE-588)4143413-4 |
| title | Text mining of web-based medical content |
| title_auth | Text mining of web-based medical content |
| title_exact_search | Text mining of web-based medical content |
| title_full | Text mining of web-based medical content |
| title_fullStr | Text mining of web-based medical content |
| title_full_unstemmed | Text mining of web-based medical content |
| title_short | Text mining of web-based medical content |
| title_sort | text mining of web based medical content |
| topic | HEALTH & FITNESS / Holism bisacsh HEALTH & FITNESS / Reference bisacsh MEDICAL / Alternative Medicine bisacsh MEDICAL / Atlases bisacsh MEDICAL / Essays bisacsh MEDICAL / Family & General Practice bisacsh MEDICAL / Holistic Medicine bisacsh MEDICAL / Osteopathy bisacsh Data mining fast Internet fast Medical informatics fast Medicine / Research fast Medizin Data mining Medicine Research Internet Medical informatics Medizinische Informatik (DE-588)4038261-8 gnd Text Mining (DE-588)4728093-1 gnd |
| topic_facet | HEALTH & FITNESS / Holism HEALTH & FITNESS / Reference MEDICAL / Alternative Medicine MEDICAL / Atlases MEDICAL / Essays MEDICAL / Family & General Practice MEDICAL / Holistic Medicine MEDICAL / Osteopathy Data mining Internet Medical informatics Medicine / Research Medizin Medicine Research Medizinische Informatik Text Mining Aufsatzsammlung |