Atjaunināt sīkdatņu piekrišanu

E-grāmata: Biomedical Informatics: Discovering Knowledge in Big Data

  • Formāts: PDF+DRM
  • Izdošanas datums: 06-May-2014
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319045283
Citas grāmatas par šo tēmu:
  • Formāts - PDF+DRM
  • Cena: 53,52 €*
  • * ši ir gala cena, t.i., netiek piemērotas nekādas papildus atlaides
  • Ielikt grozā
  • Pievienot vēlmju sarakstam
  • Šī e-grāmata paredzēta tikai personīgai lietošanai. E-grāmatas nav iespējams atgriezt un nauda par iegādātajām e-grāmatām netiek atmaksāta.
Biomedical Informatics: Discovering Knowledge in Big DataPalielināt
  • Formāts: PDF+DRM
  • Izdošanas datums: 06-May-2014
  • Izdevniecība: Springer International Publishing AG
  • Valoda: eng
  • ISBN-13: 9783319045283
Citas grāmatas par šo tēmu:

DRM restrictions

  • Kopēšana (kopēt/ievietot):

    nav atļauts

  • Drukāšana:

    nav atļauts

  • Lietošana:

    Digitālo tiesību pārvaldība (Digital Rights Management (DRM))
    Izdevējs ir piegādājis šo grāmatu šifrētā veidā, kas nozīmē, ka jums ir jāinstalē bezmaksas programmatūra, lai to atbloķētu un lasītu. Lai lasītu šo e-grāmatu, jums ir jāizveido Adobe ID. Vairāk informācijas šeit. E-grāmatu var lasīt un lejupielādēt līdz 6 ierīcēm (vienam lietotājam ar vienu un to pašu Adobe ID).

    Nepieciešamā programmatūra
    Lai lasītu šo e-grāmatu mobilajā ierīcē (tālrunī vai planšetdatorā), jums būs jāinstalē šī bezmaksas lietotne: PocketBook Reader (iOS / Android)

    Lai lejupielādētu un lasītu šo e-grāmatu datorā vai Mac datorā, jums ir nepieciešamid Adobe Digital Editions (šī ir bezmaksas lietotne, kas īpaši izstrādāta e-grāmatām. Tā nav tas pats, kas Adobe Reader, kas, iespējams, jau ir jūsu datorā.)

    Jūs nevarat lasīt šo e-grāmatu, izmantojot Amazon Kindle.

This second, revised edition examines core concepts in bioinformatics and gives readers up-to-date strategies for applying bioinformatics techniques effectively. The author covers a wealth of topics ranging from data storage to regulation and privacy.



This book provides a broad overview of the topic Bioinformatics with focus on data, information and knowledge. From data acquisition and storage to visualization, ranging through privacy, regulatory and other practical and theoretical topics, the author touches several fundamental aspects of the innovative interface between Medical and Technology domains that is Biomedical Informatics. Each chapter starts by providing a useful inventory of definitions and commonly used acronyms for each topic and throughout the text, the reader finds several real-world examples, methodologies and ideas that complement the technical and theoretical background. This new edition includes new sections at the end of each chapter, called "future outlook and research avenues," providing pointers to future challenges. At the beginning of each chapter a new section called "key problems", has been added, where the author discusses possible traps and unsolvable or major problems.
Lecture 1 Introduction: Computer Science Meets Life Science
1(56)
1 Learning Goals
1(1)
2 Advance Organizer
1(2)
3 Acronyms
3(1)
4 Key Problems
4(1)
5 Our World in Data
4(6)
6 What Is Life?
10(13)
6.1 The Building Blocks of Life
11(2)
6.2 Proteins
13(1)
6.2.1 From Amino Acids to Protein Structures
13(1)
6.2.2 Tertiary Structure of a Protein
14(1)
6.2.3 Protein Analytics
15(3)
6.3 DNA and RNA
18(2)
6.4 Cell Physiology
20(1)
6.5 Organ Systems
21(1)
6.5.1 Tissue
22(1)
6.5.2 Organs
22(1)
6.5.3 Cardiovascular System
23(1)
6.5.4 Anatomical Axes
23(1)
7 What Is Biomedical Informatics?
23(12)
7.1 Medicine Versus Informatics
23(1)
7.2 Computer Machinery
24(6)
7.3 Medical Informatics
30(1)
7.4 Biomedical Informatics
31(4)
8 Future Outlook and Research Avenues
35(5)
8.1 Grand Challenges
35(1)
8.2 Personalized Medicine
36(3)
8.3 Biomarker Discovery
39(1)
9 Exam Questions
40(6)
9.1 Yes/No Decision Questions
40(1)
9.2 Multiple Choice Questions (MCQ)
41(2)
9.3 Free Recall Block
43(3)
10 Answers
46(11)
10.1 Answers to the Yes/No Questions
46(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
47(2)
10.3 Answers to the Free Recall Questions
49(2)
References
51(6)
Lecture 2 Fundamentals of Data, Information, and Knowledge
57(52)
1 Learning Goals
57(1)
2 Advance Organizer
57(2)
3 Acronyms
59(1)
4 Key Problems
60(1)
5 Data in the Biomedical Domain
60(15)
5.1 Data Sources in Biomedical Informatics
60(1)
5.2 Levels of Data Structures
61(2)
5.3 Abstract Data Structures
63(2)
5.4 Big Data Pools in the Health Domain
65(2)
5.5 Standardization Versus Structurization
67(2)
5.6 Data Dimensionality
69(1)
5.6.1 Multivariate and Multidimensional
69(2)
5.6.2 Point Cloud Datasets
71(4)
6 A Clinical View on Data, Information, Knowledge
75(3)
7 A Closer Look on Information
78(12)
7.1 What Is Information?
78(3)
7.2 Information Entropy
81(9)
8 Future Outlook
90(4)
9 Exam Questions
94(6)
9.1 Yes/No Questions
94(1)
9.2 Multiple Choice Questions (MCQ)
95(2)
9.3 Free Recall Questions
97(3)
10 Answers
100(9)
10.1 Answers to the Yes/No Questions
100(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
101(2)
10.3 Answers to the Free Recall Questions
103(2)
References
105(4)
Lecture 3 Structured Data: Coding and Classification
109(44)
1 Learning Goals
109(1)
2 Advance Organizer
109(2)
3 Acronyms
111(1)
4 Key Problems
111(1)
5 Standardization
112(8)
5.1 The Need for Standardization in Medicine
112(1)
5.2 Inaccuracy of Medical Data
113(2)
5.3 Data Standardization
115(5)
6 Modeling Biomedical Knowledge
120(2)
7 Ontologies
122(7)
7.1 Ontology Languages
127(1)
7.2 OWL
128(1)
8 Medical Classifications
129(8)
9 Future Outlook
137(3)
10 Exam Questions
140(6)
10.1 Yes/No Questions
140(1)
10.2 Multiple Choice Questions (MCQ)
141(2)
10.3 Free Recall Questions
143(3)
11 Answers
146(7)
11.1 Answers to the Yes/No Questions
146(1)
11.2 Answers to the Multiple Choice Questions (MCQ)
147(2)
11.3 Answers to the Free Recall Questions
149(2)
References
151(2)
Lecture 4 Biomedical Databases: Acquisition, Storage, Information Retrieval, and Use
153(50)
1 Learning Goals
153(1)
2 Advance Organizer
153(3)
3 Acronyms
156(1)
4 Key Problems
157(1)
5 A First View on Hospital Information Systems
158(4)
5.1 Goals and Challenges of Hospital Information Systems
158(2)
5.2 Workflows
160(1)
5.3 Architecture of HIS
161(1)
6 Databases
162(8)
6.1 Data Warehouse
164(1)
6.2 Data Marts
164(1)
6.3 Biomedical Databanks and Cloud Computing
165(1)
6.4 Cloud Computing
165(2)
6.5 Biomedical Databases
167(3)
7 Information Retrieval
170(17)
7.1 Data Retrieval vs. Information Retrieval
171(1)
7.2 Text Retrieval
172(1)
7.3 IR Process
172(1)
7.4 Formal Notation
172(3)
7.5 Taxonomy of IR Models
175(2)
7.5.1 Set Theoretic Example: Boolean Model
177(1)
7.5.2 Example Algebraic Model: Vector Space Model
178(4)
7.5.3 Example: Probabilistic Model (Bayes' Rule)
182(5)
8 Future Outlook
187(1)
9 Exam Questions
188(6)
9.1 Yes/No Decision Questions
188(1)
9.2 Multiple Choice Questions (MCQ)
189(2)
9.3 Free Recall Block
191(3)
10 Answers
194(9)
10.1 Answers to the Yes/No Questions
194(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
195(2)
10.3 Answers to the Free Recall Questions
197(2)
References
199(4)
Lecture 5 Semi-structured, Weakly Structured, and Unstructured Data
203(48)
1 Learning Goals
203(1)
2 Advance Organizer
203(2)
3 Acronyms
205(1)
4 Key Problems
205(1)
5 Review on Data
206(7)
5.1 Well-Structured Data
208(1)
5.2 Semi-structured Data
209(2)
5.3 Weakly Structured Data
211(1)
5.4 On the Topology of Data
212(1)
6 Networks = Graphs + Data
213(21)
6.1 Networks in Biological Systems
213(1)
6.2 Network Theory
214(1)
6.2.1 Basic Concepts of Networks
214(1)
6.2.2 Computational Graph Representation
214(1)
6.2.3 Network Metrics
215(4)
6.2.4 Graphs from Point Cloud Datasets
219(6)
6.3 Network Examples
225(1)
6.3.1 The Human Brain as Network
225(1)
6.3.2 Systems Biology and Human Diseases
225(2)
6.3.3 Gene Networks
227(1)
6.4 The Essence: Three Types of Biomedical Networks
228(1)
6.4.1 Transcriptional Regulatory Networks
228(1)
6.4.2 Protein-Protein Networks
229(2)
6.4.3 Metabolic Networks
231(2)
6.5 Structural Homologies
233(1)
7 Future Outlook
234(1)
8 Exam Questions
235(6)
8.1 Yes/No Decision Questions
235(1)
8.2 Multiple Choice Questions (MCQ)
236(2)
8.3 Free Recall Block
238(3)
9 Answers
241(10)
9.1 Answers to the Yes/No Questions
241(1)
9.2 Answers to the Multiple Choice Questions (MCQ)
242(2)
9.3 Answers to the Free Recall Questions
244(3)
References
247(4)
Lecture 6 Multimedia Data Mining and Knowledge Discovery
251(48)
1 Learning Goals
251(1)
2 Advance Organizer
251(2)
3 Acronyms
253(1)
4 Key Problems
253(3)
5 Knowledge Discovery
256(4)
5.1 What Is Knowledge?
256(2)
5.2 Implicit vs. Explicit Knowledge
258(1)
5.3 Differences Between KDD and DM
258(2)
6 Data Mining Methodologies
260(20)
6.1 Definitions
260(1)
6.2 Example Tasks
261(1)
6.3 Taxonomy of Methods
261(2)
6.4 Supervised Learning
263(1)
6.4.1 Artificial Neural Networks
264(4)
6.4.2 Clinical Example: Model for End-Stage Liver Disease
268(3)
6.4.3 Bayesian Network
271(4)
6.4.4 Alterative Approach: Support Vector Machines
275(1)
6.5 Text Mining and Semantic Methods
276(1)
6.5.1 Latent Semantic Analysis
277(1)
6.5.2 Latent Dirichlet Allocation
278(1)
6.5.3 Principal Components Analysis
279(1)
7 Future Outlook
280(5)
8 Exam Questions
285(6)
8.1 Yes/No Decision Questions
285(1)
8.2 Multiple Choice Questions (MCQ)
286(2)
8.3 Free Recall Block
288(3)
9 Answers
291(8)
9.1 Answers to the Yes/No Questions
291(1)
9.2 Answers to the Multiple Choice Questions (MCQ)
292(1)
9.3 Answers to the Free Recall Questions
293(2)
References
295(4)
Lecture 7 Knowledge and Decision: Cognitive Science and Human-Computer Interaction
299(46)
1 Learning Goals
299(1)
2 Advance Organizer
299(2)
3 Acronyms
301(1)
4 Key Problems
302(1)
5 Human Information Processing
302(25)
5.1 Decision Making and Reasoning
302(2)
5.2 The Three-Storage Memory Model
304(2)
5.2.1 Example: Visual and Audial Information Processing
306(2)
5.2.2 Central Executive System
308(1)
5.2.3 Selective Attention
309(1)
5.3 Clinical Decision-Making Process
310(2)
5.4 Reasoning and Problem-Solving Procedures
312(1)
5.4.1 Hypothetico-deductive Model (HDM) vs. PCDA Deming Wheel
312(4)
5.4.2 Signal Detection Theory
316(3)
5.4.3 Differential Diagnosis
319(1)
5.4.4 Rough Set Theory (RST)
320(6)
5.4.5 Heuristic Decision Making
326(1)
6 Human Error
327(1)
7 Future Outlook
328(2)
8 Exam Questions
330(6)
8.1 Yes/No Decision Questions
330(1)
8.2 Multiple Choice Questions (MCQ)
331(2)
8.3 Free Recall Block
333(3)
9 Answers
336(9)
9.1 Answers to the Yes/No Questions
336(1)
9.2 Answers to the Multiple Choice Questions (MCQ)
337(2)
9.3 Answers to the Free Recall Questions
339(2)
References
341(4)
Lecture 8 Biomedical Decision Making: Reasoning and Decision Support
345(34)
1 Learning Goals
345(1)
2 Advance Organizer
345(2)
3 Acronyms
347(1)
4 Key Problems
347(1)
5 Decision Support Systems
348(12)
5.1 Decision Models
349(1)
5.2 Evolution of DSS
350(3)
5.3 Design Principles of DSS
353(2)
5.4 Clinical Guidelines
355(5)
6 Case-Based Reasoning
360(4)
7 Future Outlook
364(1)
8 Exam Questions
365(6)
8.1 Yes/No Decision Questions
365(1)
8.2 Multiple Choice Questions (MCQ)
366(2)
8.3 Free Recall Block
368(3)
9 Answers
371(8)
9.1 Answers to the Yes/No Questions
371(1)
9.2 Answers to the Multiple Choice Questions (MCQ)
372(2)
9.3 Answers to the Free Recall Questions
374(2)
References
376(3)
Lecture 9 Interactive Information Visualization and Visual Analytics
379(42)
1 Learning Goals
379(1)
2 Advance Organizer
379(2)
3 Acronyms
381(1)
4 Key Problems
381(1)
5 Fundamentals of Visualization Science
382(11)
5.1 Verbal Information Versus Visual Information
382(3)
5.2 Is a Picture Really Worth a Thousand Words?
385(1)
5.3 Informatics as Semiotics Engineering
386(2)
5.4 Visualization Process
388(4)
5.5 The Case of John Snow
392(1)
6 Visualization Methods
393(10)
6.1 Overview
394(1)
6.2 Parallel Coordinates
395(4)
6.3 Radial Coordinate Visualization
399(2)
6.4 Star Plots
401(2)
7 Visual Analytics
403(3)
8 Future Outlook
406(1)
9 Exam Questions
407(6)
9.1 Yes/No Decision Questions
407(1)
9.2 Multiple Choice Questions (MCQ)
408(2)
9.3 Free Recall Block
410(3)
10 Answers
413(8)
10.1 Answers to the Yes/No Questions
413(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
414(2)
10.3 Answers to the Free Recall Questions
416(2)
References
418(3)
Lecture 10 Biomedical Information Systems and Medical Knowledge Management
421(38)
1 Learning Goals
421(1)
2 Advance Organizer
421(2)
3 Acronyms
423(1)
4 Key Problems
423(1)
5 Workflow Modeling
424(8)
5.1 Workflow and Decision Support
425(1)
5.2 Formal Modeling
425(3)
5.3 Example Clinical Workflow
428(4)
5.4 Workflows in Bioinformatics
432(1)
6 Hospital Information Systems
432(2)
6.1 Architectures
433(1)
6.2 Process-Oriented Information Systems
434(1)
7 Multimedia in the Hospital
434(8)
7.1 PACS
435(1)
7.2 Data Standards (DICOM, HL7, LOINC)
436(6)
8 Future Outlook
442(3)
9 Exam Questions
445(6)
9.1 Yes/No-Decision Questions
445(1)
9.2 Multiple Choice Questions (MCQ)
446(2)
9.3 Free Recall Block
448(3)
10 Answers
451(8)
10.1 Answers to the Yes/No Questions
451(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
452(2)
10.3 Answers to the Free Recall Questions
454(2)
References
456(3)
Lecture 11 Biomedical Data: Privacy, Safety, and Security
459(42)
1 Learning Goals
459(1)
2 Advance Organizer
459(2)
3 Acronyms
461(1)
4 Key Problems
462(1)
5 Standardization and Health Care
463(12)
5.1 What Is Risk?
463(1)
5.2 The IOM Report
464(2)
5.3 Medical Error
466(1)
5.3.1 Eindhoven Classification Model
466(1)
5.3.2 Adverse Event Reporting
467(1)
5.3.3 Human Error
468(1)
5.3.4 Risk Management
468(2)
5.3.5 Ubiquitous Devices
470(1)
5.3.6 Context-Aware Patient Safety
471(2)
5.4 Safety, Security and Technical Dependability
473(2)
6 Patient Data Privacy
475(5)
7 Private Personal Health Record
480(6)
8 Future Outlook
486(1)
9 Exam Questions
487(6)
9.1 Yes/No Decision Questions
487(1)
9.2 Multiple Choice Questions (MCQ)
488(2)
9.3 Free Recall Block
490(3)
10 Answers
493(8)
10.1 Answers to the Yes/No Questions
493(1)
10.2 Answers to the Multiple Choice Questions (MCQ)
494(2)
10.3 Answers to the Free Recall Questions
496(2)
References
498(3)
Lecture 12 Methodology for Information Systems: System Design, Usability, and Evaluation
501(46)
1 Learning Goals
501(1)
2 Advance Organizer
501(4)
3 Acronyms
505(1)
4 Key Problems
506(1)
5 A Framework for Understanding Usability
507(2)
6 Standards
509(7)
6.1 EU Directive: Medical Device Directive
510(1)
6.2 ISO Standards
511(3)
6.3 Quality Management Process Cycle
514(1)
6.4 Software Product Quality Model
515(1)
7 Usability Engineering
516(9)
7.1 Usability Engineering Methods
516(1)
7.2 How to Measure Usability?
517(1)
7.2.1 The System Usability Scale (SUS)
517(1)
7.2.2 The Software Usability Measurement Inventory (SUMI)
518(1)
7.2.3 Usability Measurement Metrics
518(1)
7.3 User-Centered Design and Development
519(6)
8 Evaluation
525(1)
9 Technology Acceptance
526(1)
10 Future Outlook
527(3)
11 Exam Questions
530(6)
11.1 Yes/No Decision Questions
530(1)
11.2 Multiple Choice Questions (MCQ)
531(2)
11.3 Free Recall Block
533(3)
12 Answers
536(11)
12.1 Answers to the Yes/No Questions
536(1)
12.2 Answers to the Multiple Choice Questions (MCQ)
537(2)
12.3 Answers to the Free Recall Questions
539(2)
References
541(6)
Index 547
Dr. Holzinger is Head of Research Unit HCI4MED, Institute of Medical Informatics, Statistics and Documentation, Medical University Graz and is an Assoc. Prof. for Information Processing, Faculty of Informatics, Graz University of Technology; Lecturer for Biomedical Informatics, Faculty of Electrical Engineering, Graz University of Technology.
Biežāk uzdotie jautājumi par e-grāmatām Biežāk uzdotie jautājumi par e-grāmatām
Permanent link: https://www.kriso.lv/db/97833190452832e.html
Keywords: