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Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book¿s promise is ¿no math, no code¿and will explain the topics in a style that is optimized for a healthcare audience.
Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book¿s promise is ¿no math, no code¿and will explain the topics in a style that is optimized for a healthcare audience.
Pieter Kubben is a neurosurgeon, mobile app developer and programme manager for eHealth and mHealth for the Maastricht University Medical Center. Telemonitoring and corresponding algorithm development is a particular focus area Dr Kubben is involved in, as well as interactive clinical decision support systems.
Michel Dumontier is a distuinguished professor of data science at Maastricht University and head of the Institute for Data Science ¿ connecting data science initiatives and projects from all faculties. He is also deeply involved in the FAIR data approach (Findable, Accessible, Interoperable, Reproducible).
André Dekker is a professor of clinical data science at Maastricht University and has been leading the development of prediction models in radiation therapy for many years. He is also coordinator of the Personal Health Train project, aiming to facilitate ¿citizen science¿.
Provides a resource for healthcare professionals on smart algorithms
Integrates the data, modelling, clinical application levels of clinical data science
Focuses on relevant non math and code aspects for physicians
Data sources.- Data at scale.- Standards in healthcare data.- Using FAIR data / data stewardship.- Privacy / deidentification.- Preparing your data.- Creating a predictive model.- Diving deeper into models.- Validation and Evaluation of reported models.- Clinical decision support systems.- Mobile app development.- Operational excellence.- Value Based Healthcare (Regulatory concerns).
| Erscheinungsjahr: | 2019 |
|---|---|
| Fachbereich: | Allgemeine Lexika |
| Genre: | Medizin |
| Rubrik: | Wissenschaften |
| Medium: | Buch |
| Seiten: | 232 |
| Inhalt: |
viii
219 S. 10 s/w Illustr. 35 farbige Illustr. 219 p. 45 illus. 35 illus. in color. |
| ISBN-13: | 9783319997124 |
| ISBN-10: | 3319997122 |
| Sprache: | Englisch |
| Herstellernummer: | 978-3-319-99712-4 |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: |
Kubben, Pieter
Dumontier, Michel Dekker, Andre |
| Redaktion: |
Kubben, Pieter
Dekker, Andre Dumontier, Michel |
| Herausgeber: | Pieter Kubben/Michel Dumontier/Andre Dekker |
| Auflage: | 1st ed. 2019 |
| Hersteller: | Springer International Publishing |
| Maße: | 241 x 160 x 18 mm |
| Von/Mit: | Pieter Kubben (u. a.) |
| Erscheinungsdatum: | 07.01.2019 |
| Gewicht: | 0,56 kg |
Pieter Kubben is a neurosurgeon, mobile app developer and programme manager for eHealth and mHealth for the Maastricht University Medical Center. Telemonitoring and corresponding algorithm development is a particular focus area Dr Kubben is involved in, as well as interactive clinical decision support systems.
Michel Dumontier is a distuinguished professor of data science at Maastricht University and head of the Institute for Data Science ¿ connecting data science initiatives and projects from all faculties. He is also deeply involved in the FAIR data approach (Findable, Accessible, Interoperable, Reproducible).
André Dekker is a professor of clinical data science at Maastricht University and has been leading the development of prediction models in radiation therapy for many years. He is also coordinator of the Personal Health Train project, aiming to facilitate ¿citizen science¿.
Provides a resource for healthcare professionals on smart algorithms
Integrates the data, modelling, clinical application levels of clinical data science
Focuses on relevant non math and code aspects for physicians
Data sources.- Data at scale.- Standards in healthcare data.- Using FAIR data / data stewardship.- Privacy / deidentification.- Preparing your data.- Creating a predictive model.- Diving deeper into models.- Validation and Evaluation of reported models.- Clinical decision support systems.- Mobile app development.- Operational excellence.- Value Based Healthcare (Regulatory concerns).
| Erscheinungsjahr: | 2019 |
|---|---|
| Fachbereich: | Allgemeine Lexika |
| Genre: | Medizin |
| Rubrik: | Wissenschaften |
| Medium: | Buch |
| Seiten: | 232 |
| Inhalt: |
viii
219 S. 10 s/w Illustr. 35 farbige Illustr. 219 p. 45 illus. 35 illus. in color. |
| ISBN-13: | 9783319997124 |
| ISBN-10: | 3319997122 |
| Sprache: | Englisch |
| Herstellernummer: | 978-3-319-99712-4 |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: |
Kubben, Pieter
Dumontier, Michel Dekker, Andre |
| Redaktion: |
Kubben, Pieter
Dekker, Andre Dumontier, Michel |
| Herausgeber: | Pieter Kubben/Michel Dumontier/Andre Dekker |
| Auflage: | 1st ed. 2019 |
| Hersteller: | Springer International Publishing |
| Maße: | 241 x 160 x 18 mm |
| Von/Mit: | Pieter Kubben (u. a.) |
| Erscheinungsdatum: | 07.01.2019 |
| Gewicht: | 0,56 kg |
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