Clinical Research Computing: A Practitioner's Handbook
Autor Prakash Nadkarnien Limba Engleză Paperback – 26 apr 2016
- Offers case studies, based on real-life examples where possible, to engage the readers with more complex examples
- Provides studies backed by technical details, e.g., schema diagrams, code snippets or algorithms illustrating particular techniques, to give the readers confidence to employ the techniques described in their own settings
- Offers didactic content organization and an increasing complexity through the chapters
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Specificații
ISBN-13: 9780128031308
ISBN-10: 0128031301
Pagini: 240
Dimensiuni: 191 x 235 x 16 mm
Greutate: 0.52 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128031301
Pagini: 240
Dimensiuni: 191 x 235 x 16 mm
Greutate: 0.52 kg
Editura: ELSEVIER SCIENCE
Cuprins
1. Foreword
2. An Introduction to Clinical Research Concepts
3. Clinical Research Processes: Technological and Non-technological considerations
4. Core Informatics Technologies
5. Software for Patient Care vs. Software for Research Support: Similarities and Differences
6. Software for Research Data Capture, Storage: Using Clinical Research Information Systems
7. Data Security and Privacy Issues
8. Mobile Technologies
9. Using Electronic Health Record Technology to Support Research: Institutional and Personal Health Records
10. Data Resources: Clinical Repositories, Warehouses and Registries, Standards in Clinical Research
11. Big Data Analytics and Data Mining
12. Conclusions
2. An Introduction to Clinical Research Concepts
3. Clinical Research Processes: Technological and Non-technological considerations
4. Core Informatics Technologies
5. Software for Patient Care vs. Software for Research Support: Similarities and Differences
6. Software for Research Data Capture, Storage: Using Clinical Research Information Systems
7. Data Security and Privacy Issues
8. Mobile Technologies
9. Using Electronic Health Record Technology to Support Research: Institutional and Personal Health Records
10. Data Resources: Clinical Repositories, Warehouses and Registries, Standards in Clinical Research
11. Big Data Analytics and Data Mining
12. Conclusions