Text mining of web-based medical content / / edited by Amy Neustein

• Record Nr.: UNINA9910464166903321
• Pubbl/distr/stampa: Berlin : , : Boston : , : De Gruyter, , [2014]; ©2014
• ISBN: 1-61451-390-2; 1-61451-976-5
• Descrizione fisica: 1 online resource (286 p.)
• Collana: Speech technology and text mining in medicine and healthcare ; ; volume 1
• Disciplina: 610.285/6
• Soggetti: Data mining; Medicine - Research; Internet; Medical informatics; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references.
• Nota di contenuto: Front matter -- 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 / Neustein, Amy / Imambi, S. Sagar / Rodrigues, Mário / Teixeira, António / Ferreira, Liliana -- 2. Unlocking information in electronic health records using natural language processing: a case study in medication information extraction / Xu, Hua / Joshua, C. Denny -- 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 / Teixeira, António / Ferreira, Liliana / Rodrigues, Mário -- 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 / Chartree, Jedsada / Angel, Bravo-Salgado / Jimenez, Tamara / Armin, R. Mikler -- 5. A study of personal health ; information posted online: using machine learning to validate the importance of the terms detected by MedDRA and SNOMED in revealing health information in social media / Ghazinour, Kambiz / Sokolova, Marina / Matwin, Stan -- 6. Twitter for health - building a social media search engine to better understand and curate laypersons' personal experiences / Suominen, Hanna / Hanlen, Leif / Cécile, Paris -- Part III. Using speech and audio technologies for improving access to online content for the computer-illiterate and the visually impaired -- 7. An empirical study of user satisfaction with a health dialogue system designed for the Nigerian low-literate, computer-illiterate, and visually impaired / Oyelami, Olufemi -- 8. DVX - the descriptive video exchange project: using crowd-based audio clips to improve online video access for the blind and the visually impaired / Keith, M. Williams -- Part IV. Visual data: new methods and approaches to mining radiographic image data and video metadata -- 9. Information extraction from medical images: evaluating a novel automatic image annotation system using semantic-based visual information retrieval / Dumitru, Dan Burdescu / Stanescu, Liana / Brezovan, Marius -- 10. Helping patients in performing online video search: evaluating the importance of medical terminology extracted from MeSH and ICD-10 in health video title and description / Karlsen, Randi / Enrique, Jose / Morell, Borrás / Johan, Gustav Bellika / Vicente, Traver Salcedo -- Editor's biography
• Sommario/riassunto: • Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.• Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.• Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform information extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:• Clinical Documents in Electronic Health Records• Summarization Techniques for Online Health Data• Natural Language Processing for Text Mining• Query Expansion Techniques for Tweets• Online Video Data Retrieval of Health-Related Videos• Dengue Fever Outbreaks• Bioemergencies and Social Media Posts• Speech-based Disease Screening for Malaria, Yellow Fever, Typhoid, and Lassa Fever• Audio Access to Online Video Data for the Visually Impaired; • Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature.• Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing.• Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, ; query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform information extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include:• Mining Biomedical Literature and Clinical Narratives • Medication Information Extraction • Machine Learning Techniques for Mining Medical Search Queries • Detecting the Level of Personal Health Information Revealed in Social Media • Curating Layperson's Personal Experiences with Health Care from Social Media and Twitter • Health Dialogue Systems for Improving Access to Online Content • Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired • Semantic-based Visual Information Retrieval for Mining Radiographic Image Data • Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions

Triticale / / Robert A. Forsberg, editor ; sponsored by Crop Science Society of America

• Record Nr.: UNINA9910643439303321
• Pubbl/distr/stampa: Madison, Wisconsin : , : Crop Science Society of America : , : American Society of Agronomy, , 1985
• ISBN: 0-89118-588-7
• Descrizione fisica: 1 online resource (vii, 82 pages)
• Collana: CSSA Special Publication ; ; Number 9
• Disciplina: 633.112
• Soggetti: Triticale
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Leading edge techniques in forensic trace evidence analysis : more new trace analysis methods / / edited by Robert D. Blackledge

• Record Nr.: UNINA9910643275703321
• Pubbl/distr/stampa: Hoboken, New Jersey : , : Wiley, , [2023]; ©2023
• ISBN: 1-119-59172-4; 1-119-59183-X
• Descrizione fisica: 1 online resource (371 pages)
• Disciplina: 363.25/6
• Soggetti: Trace evidence
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Foreword -- Preface -- Chapter 1 Forensic Analysis of Shimmer ; Particles in Cosmetic Samples -- 1.1 Introduction -- 1.2 What is Shimmer? -- 1.2.1 Shimmer versus Glitter -- 1.2.2 Shimmer Composition and Use -- 1.3 Shimmer Detection and Collection -- 1.3.1 Detection of Cosmetic Stains -- 1.3.2 Collection of Shimmer Particles -- 1.4 Analysis of Shimmer Particles -- 1.4.1 Sample Extraction and Preparation -- 1.4.2 Digital Microscopy -- 1.4.3 Infrared Spectroscopy -- 1.4.4 Raman Spectroscopy -- 1.4.5 X‐Ray Diffraction -- 1.4.6 Scanning Electron Microscopy - Energy Dispersive X‐Ray Spectroscopy -- 1.5 Ideal Contact Trace -- 1.5.1 Nearly Invisible -- 1.5.2 High Probability of Transfer and Retention -- 1.5.3 Highly Individualistic -- 1.5.4 Easily Collected, Separated, and Concentrated -- 1.5.5 Mere Traces Easily Characterized -- 1.5.6 Searchable via Computerized Database -- 1.5.7 Will Survive Most Environmental Insults -- 1.6 Case Examples -- 1.7 Conclusion -- Acknowledgments -- References -- Chapter 2 Glitter and Other Flake Pigments -- 2.1 Introduction -- 2.2 Glitter Update -- 2.3 Cutting Film into Individual Glitter Particles -- 2.4 Reflectance -- 2.5 Embossed Effects -- 2.6 Color -- 2.7 Specific Gravity -- 2.8 Is It Glitter or a Flake Pigment? -- 2.9 Materials and Processes that Have Been Used to Produce Flake Materials -- 2.9.1 Post Manufacture Modification -- 2.9.2 Polymer Film Flakes - Differences that May Help Discriminate the Flake Source -- 2.9.3 Foil -- 2.9.4 Flake Materials -- 2.9.5 Natural Materials -- 2.9.6 Synthetic Materials -- 2.9.7 Freestanding Flakes -- 2.9.8 Effects -- 2.9.9 Post Manufacture Modification -- 2.9.10 Color -- 2.9.11 Discriminating Between Flakes of Unknown Origin -- 2.9.12 Follow the Yellow Brick Road -- References.; Chapter 3 X‐ray Photoelectron Spectroscopy -- 3.1 Introduction -- 3.2 Background and Theory -- 3.3 Instrumentation -- 3.3.1 Ultra‐High Vacuum (UHV) -- 3.3.2 X‐ray Source -- 3.3.3 Electron Detector -- 3.3.4 Charge Compensation Source -- 3.3.5 Sample Cleaning - Monatomic Ions -- 3.3.6 Depth Profiling -- 3.3.7 Sample Preparation -- 3.4 Argon‐Ion Cluster Beam Technology -- 3.5 Evidence Type Examples -- 3.5.1 Example 1: Surface Modified Fibers -- 3.5.2 Example 2: Glass -- 3.5.2.1 A -- 3.5.2.2 B -- 3.5.3 Example 3: Hair Fibers with Modifications -- 3.6 Future Directions of XPS and Forensics -- 3.6.1 HAXPES -- 3.6.2 NAPXPS -- 3.7 Conclusions -- Acknowledgements -- References -- Chapter 4 Density Determination and Separation via Magnetic Levitation -- 4.1 Introduction -- 4.2 Objectives of the Work -- 4.3 Guidance to the Reader -- 4.4 Theoretical Basis* -- 4.4.1 What Is MAGLEV? -- 4.4.2 Brief Discussion of Trace Evidence Separation Methods and their Limitations -- 4.4.3 Brief Discussion of Density and Determination Methods -- 4.4.4 Detailed Discussion of Theory* -- 4.5 Preparation for Density Determination Via MAGLEV -- 4.5.1 Choosing the Type of MAGLEV Device: Precision, Accuracy, Working Distance, Sensitivity, and Range of Density -- 4.5.2 Testing the Compatibility Between Trace Evidence and Paramagnetic Media -- 4.5.3 Analysis of Nonpolar Compounds Using MAGLEV -- 4.5.4 Analysis of Polar Compounds Using MAGLEV -- 4.5.5 Calibration -- 4.6 Protocols for Measurement of Density, and Separation Using MAGLEV -- 4.6.1 Basic Protocol for Typical Use of the MAGLEV Device -- 4.6.2 Troubleshooting the Experiments -- 4.7 Trace‐Evidence‐Like Materials That Have Been Analyzed with MAGLEV -- 4.7.1 Bone -- 4.7.2 Glitter and Gunpowder -- 4.7.3 Powdered Drugs, Polymorphs, and Enantiomers -- 4.7.4 Glass -- 4.7.5 Polymers -- 4.7.6 Hair and Dandruff.; 4.8 Instructions for the Construction of MAGLEV Devices -- 4.9 Conclusion -- References -- Chapter 5 Forensic Applications of Gas Chromatography - Vacuum Ultraviolet Spectroscopy Paired with Mass ; Spectrometry -- 5.1 Introduction -- 5.2 Background of Mass Spectrometry -- 5.3 Background of Vacuum Ultraviolet Spectroscopy -- 5.4 Combining GC/VUV and GC/MS -- 5.5 Analysis of Fentanyl Analogues -- 5.6 Analysis of Smokeless Powders -- 5.7 Analysis of Lipstick -- 5.8 Analysis of Blood Alcohol Content and Inhalants -- 5.9 Analysis of Fire Debris Samples -- 5.10 Conclusion -- References -- Chapter 6 Surface Acoustic Wave Nebulization‐Mass Spectrometry -- 6.1 Theory and Instrumentation -- 6.2 Analysis of Complex Samples -- 6.2.1 Single Fibers Having Synthetic Organic Dyes and Other Trace Evidence Examples -- 6.2.2 The Case of Denim Fibers -- 6.2.3 From Natural to Synthetic Indigo for Denim Dyeing -- 6.2.3.1 MS and Denim Analysis -- References -- Chapter 7 Elemental Imaging of Forensic Traces with Macro‐ and Micro‐XRF -- 7.1 Introduction -- 7.2 XRF Imaging Methods and Instrumentation -- 7.3 Elemental Imaging of Gun Shot Residues -- 7.4 Using Elemental Markers to Detect and Image Biological Traces -- 7.5 Visualizing Cosmetic and Personal Care Product Stains -- 7.6 Noninvasive Imaging of Hidden and Concealed Forensic Traces -- 7.7 Future Outlook -- Acknowledgments -- References -- Chapter 8 Characterization of Human Head Hairs via Proteomics -- 8.1 Introduction -- 8.2 Human Hair -- 8.2.1 Structure and Role -- 8.2.2 Growth Cycle -- 8.2.3 Chemical Composition -- 8.3 Human Hair as Forensic Evidence: The Investigative Value of Hair -- 8.3.1 Physical Hair Analysis Workflow -- 8.3.2 Microscopy (Physical) in Conjunction with DNA (Chemical) Analysis -- 8.4 Current and Emerging Proteomic Methods for Forensic Human Hair Analysis.; 8.4.1 Applicability of SAPs and GVPs in Hair Analysis -- 8.5 Current and Emerging Methods for Forensic Human Hair Analysis -- 8.5.1 Nano‐Liquid Chromatography (nLC) with Electrospray Ionization and MS/MS -- 8.5.2 Proteomics Analysis with Tandem/Hybrid Mass Spectrometry -- 8.5.3 Hair Proteome Sequencing Via CE‐MS/MS -- 8.6 Challenges to Implementing Protein Sequencing in Forensic Casework -- 8.6.1 Triage of Evidence and Prioritization for Examination -- 8.6.2 Need for Validated Protocols and Appropriate Quality Assurance/Quality Control Procedures -- 8.6.3 Not Amenable to Databasing vis‐a‐vis CODIS -- 8.6.4 Variable Protein Expression -- 8.7 Conclusion -- Acknowledgments -- References -- Chapter 9 Photo‐induced Force Microscopy -- 9.1 Introduction -- 9.2 Working Principle and Instrumentation -- 9.3 Trace Evidence Examples -- 9.3.1 Fibers -- 9.3.2 Nanoscale Chemical Mapping -- 9.3.3 Individual Glitter and Shimmer Particles -- References -- Chapter 10 Raman and Surface‐Enhanced Raman Scattering (SERS) for Trace Analysis -- 10.1 Introduction -- 10.2 Theory -- 10.2.1 Raman Spectroscopy -- 10.2.2 Enhancement Mechanism in SERS -- 10.2.3 SERS Substrates -- 10.2.4 Probe Molecules -- 10.3 Instrumentation -- 10.3.1 Spectrometer -- 10.3.2 Excitation Lasers -- 10.3.3 Detector -- 10.3.4 Microscope -- 10.3.5 Portable Spectrometers -- 10.4 Forensic Applications -- 10.4.1 Questioned Document -- 10.4.2 Explosives -- 10.4.3 Fibers -- 10.4.4 Paint -- 10.4.5 Fingermarks -- 10.4.6 Fire Accelerants -- 10.4.7 Gunshot Residues -- 10.4.8 Cosmetic Products -- 10.4.9 Other Types of Physical Evidence -- References -- Index -- EULA.