Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care
"In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Neustein, Amy [verfasserIn] Christen, Nathaniel [verfasserIn] |
|---|
| Format: |
E-Book |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
London: Academic Press, an imprint of Elsevier ; 2022 2022 |
|---|
| Anmerkung: |
Includes bibliographical references and index |
|---|---|
| Umfang: |
1 Online-Ressource (vii, 278 pages) |
| Links: | |
|---|---|
| ISBN: |
978-0-323-85356-9 0-323-85356-0 |
| Katalog-ID: |
1876381094 |
|---|
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| 245 | 1 | 0 | |a Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care |c Amy Neustein, Nathaniel Christen |
| 264 | 1 | |a London |b Academic Press, an imprint of Elsevier |c [2022] | |
| 264 | 4 | |c 2022 | |
| 300 | |a 1 Online-Ressource (vii, 278 pages) | ||
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| 500 | |a Includes bibliographical references and index | ||
| 505 | 8 | 0 | |a 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. |
| 520 | |a "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- | ||
| 650 | 0 | |a Medical care |x Data processing | |
| 650 | 0 | |a Data integration (Computer science) | |
| 650 | 0 | |a COVID-19 (Disease) |x Treatment | |
| 650 | 0 | |a Cancer |x Treatment | |
| 650 | 0 | |a Cardiovascular system |x Diseases |x Treatment | |
| 650 | 2 | |a Medical Informatics |0 (DNLM)D008490 | |
| 650 | 2 | |a COVID-19 |x therapy |0 (DNLM)D000086382Q000628 | |
| 650 | 2 | |a Neoplasms |x therapy |0 (DNLM)D009369Q000628 | |
| 650 | 2 | |a Cardiovascular Diseases |x therapy |0 (DNLM)D002318Q000628 | |
| 650 | 4 | |a Integration de donnees (Informatique) |0 (CaQQLa)000275620 | |
| 650 | 4 | |a COVID-19 - Traitement |0 (CaQQLa)000313216 | |
| 650 | 4 | |a Cancer - Traitement |0 (CaQQLa)201-0004693 | |
| 650 | 4 | |a Appareil cardiovasculaire - Maladies - Traitement |0 (CaQQLa)201-0233264 | |
| 650 | 4 | |a Soins medicaux - Informatique |0 (CaQQLa)201-0052619 | |
| 650 | 4 | |a Medecine - Informatique |0 (CaQQLa)201-0103112 | |
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| 650 | 4 | |a COVID-19 (Disease) - Treatment |0 (OCoLC)fst01984645 | |
| 650 | 4 | |a Data integration (Computer science) |0 (OCoLC)fst01763872 | |
| 650 | 4 | |a Medical care - Data processing |0 (OCoLC)fst01013786 | |
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9780323853569 electronic book 978-0-323-85356-9 0323853560 electronic book 0-323-85356-0 (DE-627)1876381094 (DE-599)KEP099620359 (ELSEVIER)on1293025077 (EBP)099620359 DE-627 eng DE-627 rda eng XA-GB R858 610.285 23 Neustein, Amy verfasserin aut Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care Amy Neustein, Nathaniel Christen London Academic Press, an imprint of Elsevier [2022] 2022 1 Online-Ressource (vii, 278 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Medical care Data processing Data integration (Computer science) COVID-19 (Disease) Treatment Cancer Treatment Cardiovascular system Diseases Treatment Medical Informatics (DNLM)D008490 COVID-19 therapy (DNLM)D000086382Q000628 Neoplasms therapy (DNLM)D009369Q000628 Cardiovascular Diseases therapy (DNLM)D002318Q000628 Integration de donnees (Informatique) (CaQQLa)000275620 COVID-19 - Traitement (CaQQLa)000313216 Cancer - Traitement (CaQQLa)201-0004693 Appareil cardiovasculaire - Maladies - Traitement (CaQQLa)201-0233264 Soins medicaux - Informatique (CaQQLa)201-0052619 Medecine - Informatique (CaQQLa)201-0103112 Cancer - Treatment (OCoLC)fst00845538 Cardiovascular system - Diseases - Treatment (OCoLC)fst00847218 COVID-19 (Disease) - Treatment (OCoLC)fst01984645 Data integration (Computer science) (OCoLC)fst01763872 Medical care - Data processing (OCoLC)fst01013786 Christen, Nathaniel verfasserin aut 9780323851978 paperback 0323851975 paperback Erscheint auch als Druck-Ausgabe NEUSTEIN, AMY INNOVATIVE DATA INTEGRATION AND CONCEPTUAL SPACE MODELING FOR COVID, CANCER, AND CARDIAC CARE ELSEVIER ACADEMIC PRESS, 2022 0323851975 https://www.sciencedirect.com/science/book/9780323851978 X:ELSEVIER Verlag lizenzpflichtig BSZ-33-EBS-HSAA ZDB-33-ESD BSZ-33-ESD-L1FH ZDB-33-EGE 2022 GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 610.285 60 01 0705 450439636X 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 27-03-24 132 01 0959 4506287444 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 02-04-24 185 01 3519 4514771945 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540288016 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520341329 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467488618 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4440938809 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 19-12-23 60 01 0705 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780323851978 185 01 3519 https://www.sciencedirect.com/science/book/9780323851978 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323851978 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780323851978 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323851978 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 00 EBooks Elsevier Engineering 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier |
| spelling |
9780323853569 electronic book 978-0-323-85356-9 0323853560 electronic book 0-323-85356-0 (DE-627)1876381094 (DE-599)KEP099620359 (ELSEVIER)on1293025077 (EBP)099620359 DE-627 eng DE-627 rda eng XA-GB R858 610.285 23 Neustein, Amy verfasserin aut Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care Amy Neustein, Nathaniel Christen London Academic Press, an imprint of Elsevier [2022] 2022 1 Online-Ressource (vii, 278 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Medical care Data processing Data integration (Computer science) COVID-19 (Disease) Treatment Cancer Treatment Cardiovascular system Diseases Treatment Medical Informatics (DNLM)D008490 COVID-19 therapy (DNLM)D000086382Q000628 Neoplasms therapy (DNLM)D009369Q000628 Cardiovascular Diseases therapy (DNLM)D002318Q000628 Integration de donnees (Informatique) (CaQQLa)000275620 COVID-19 - Traitement (CaQQLa)000313216 Cancer - Traitement (CaQQLa)201-0004693 Appareil cardiovasculaire - Maladies - Traitement (CaQQLa)201-0233264 Soins medicaux - Informatique (CaQQLa)201-0052619 Medecine - Informatique (CaQQLa)201-0103112 Cancer - Treatment (OCoLC)fst00845538 Cardiovascular system - Diseases - Treatment (OCoLC)fst00847218 COVID-19 (Disease) - Treatment (OCoLC)fst01984645 Data integration (Computer science) (OCoLC)fst01763872 Medical care - Data processing (OCoLC)fst01013786 Christen, Nathaniel verfasserin aut 9780323851978 paperback 0323851975 paperback Erscheint auch als Druck-Ausgabe NEUSTEIN, AMY INNOVATIVE DATA INTEGRATION AND CONCEPTUAL SPACE MODELING FOR COVID, CANCER, AND CARDIAC CARE ELSEVIER ACADEMIC PRESS, 2022 0323851975 https://www.sciencedirect.com/science/book/9780323851978 X:ELSEVIER Verlag lizenzpflichtig BSZ-33-EBS-HSAA ZDB-33-ESD BSZ-33-ESD-L1FH ZDB-33-EGE 2022 GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 610.285 60 01 0705 450439636X 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 27-03-24 132 01 0959 4506287444 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 02-04-24 185 01 3519 4514771945 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540288016 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520341329 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467488618 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4440938809 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 19-12-23 60 01 0705 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780323851978 185 01 3519 https://www.sciencedirect.com/science/book/9780323851978 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323851978 2020 01 DE-Ch1 https://www.sciencedirect.com/science/book/9780323851978 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323851978 2111 01 DE-944 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 00 EBooks Elsevier Engineering 132 01 0959 EBS Elsevier 185 01 3519 OLR-EBS 370 01 4370 EBS Elsevier |
| allfields_unstemmed |
9780323853569 electronic book 978-0-323-85356-9 0323853560 electronic book 0-323-85356-0 (DE-627)1876381094 (DE-599)KEP099620359 (ELSEVIER)on1293025077 (EBP)099620359 DE-627 eng DE-627 rda eng XA-GB R858 610.285 23 Neustein, Amy verfasserin aut Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care Amy Neustein, Nathaniel Christen London Academic Press, an imprint of Elsevier [2022] 2022 1 Online-Ressource (vii, 278 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Medical care Data processing Data integration (Computer science) COVID-19 (Disease) Treatment Cancer Treatment Cardiovascular system Diseases Treatment Medical Informatics (DNLM)D008490 COVID-19 therapy (DNLM)D000086382Q000628 Neoplasms therapy (DNLM)D009369Q000628 Cardiovascular Diseases therapy (DNLM)D002318Q000628 Integration de donnees (Informatique) (CaQQLa)000275620 COVID-19 - Traitement (CaQQLa)000313216 Cancer - Traitement (CaQQLa)201-0004693 Appareil cardiovasculaire - Maladies - Traitement (CaQQLa)201-0233264 Soins medicaux - Informatique (CaQQLa)201-0052619 Medecine - Informatique (CaQQLa)201-0103112 Cancer - Treatment (OCoLC)fst00845538 Cardiovascular system - Diseases - Treatment (OCoLC)fst00847218 COVID-19 (Disease) - Treatment (OCoLC)fst01984645 Data integration (Computer science) (OCoLC)fst01763872 Medical care - Data processing (OCoLC)fst01013786 Christen, Nathaniel verfasserin aut 9780323851978 paperback 0323851975 paperback Erscheint auch als Druck-Ausgabe NEUSTEIN, AMY INNOVATIVE DATA INTEGRATION AND CONCEPTUAL SPACE MODELING FOR COVID, CANCER, AND CARDIAC CARE ELSEVIER ACADEMIC PRESS, 2022 0323851975 https://www.sciencedirect.com/science/book/9780323851978 X:ELSEVIER Verlag lizenzpflichtig BSZ-33-EBS-HSAA ZDB-33-ESD BSZ-33-ESD-L1FH ZDB-33-EGE 2022 GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 610.285 60 01 0705 450439636X 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 27-03-24 132 01 0959 4506287444 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 02-04-24 185 01 3519 4514771945 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540288016 EBS Elsevier Vervielfältigungen (z.B. 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Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Medical care Data processing Data integration (Computer science) COVID-19 (Disease) Treatment Cancer Treatment Cardiovascular system Diseases Treatment Medical Informatics (DNLM)D008490 COVID-19 therapy (DNLM)D000086382Q000628 Neoplasms therapy (DNLM)D009369Q000628 Cardiovascular Diseases therapy (DNLM)D002318Q000628 Integration de donnees (Informatique) (CaQQLa)000275620 COVID-19 - Traitement (CaQQLa)000313216 Cancer - Traitement (CaQQLa)201-0004693 Appareil cardiovasculaire - Maladies - Traitement (CaQQLa)201-0233264 Soins medicaux - Informatique (CaQQLa)201-0052619 Medecine - Informatique (CaQQLa)201-0103112 Cancer - Treatment (OCoLC)fst00845538 Cardiovascular system - Diseases - Treatment (OCoLC)fst00847218 COVID-19 (Disease) - Treatment (OCoLC)fst01984645 Data integration (Computer science) (OCoLC)fst01763872 Medical care - Data processing (OCoLC)fst01013786 Christen, Nathaniel verfasserin aut 9780323851978 paperback 0323851975 paperback Erscheint auch als Druck-Ausgabe NEUSTEIN, AMY INNOVATIVE DATA INTEGRATION AND CONCEPTUAL SPACE MODELING FOR COVID, CANCER, AND CARDIAC CARE ELSEVIER ACADEMIC PRESS, 2022 0323851975 https://www.sciencedirect.com/science/book/9780323851978 X:ELSEVIER Verlag lizenzpflichtig BSZ-33-EBS-HSAA ZDB-33-ESD BSZ-33-ESD-L1FH ZDB-33-EGE 2022 GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 610.285 60 01 0705 450439636X 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 27-03-24 132 01 0959 4506287444 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 02-04-24 185 01 3519 4514771945 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540288016 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520341329 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467488618 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4440938809 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 19-12-23 60 01 0705 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780323851978 185 01 3519 https://www.sciencedirect.com/science/book/9780323851978 370 01 4370 E-Book: Zugriff im HCU-Netz. 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9780323853569 electronic book 978-0-323-85356-9 0323853560 electronic book 0-323-85356-0 (DE-627)1876381094 (DE-599)KEP099620359 (ELSEVIER)on1293025077 (EBP)099620359 DE-627 eng DE-627 rda eng XA-GB R858 610.285 23 Neustein, Amy verfasserin aut Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care Amy Neustein, Nathaniel Christen London Academic Press, an imprint of Elsevier [2022] 2022 1 Online-Ressource (vii, 278 pages) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes bibliographical references and index 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. "In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Medical care Data processing Data integration (Computer science) COVID-19 (Disease) Treatment Cancer Treatment Cardiovascular system Diseases Treatment Medical Informatics (DNLM)D008490 COVID-19 therapy (DNLM)D000086382Q000628 Neoplasms therapy (DNLM)D009369Q000628 Cardiovascular Diseases therapy (DNLM)D002318Q000628 Integration de donnees (Informatique) (CaQQLa)000275620 COVID-19 - Traitement (CaQQLa)000313216 Cancer - Traitement (CaQQLa)201-0004693 Appareil cardiovasculaire - Maladies - Traitement (CaQQLa)201-0233264 Soins medicaux - Informatique (CaQQLa)201-0052619 Medecine - Informatique (CaQQLa)201-0103112 Cancer - Treatment (OCoLC)fst00845538 Cardiovascular system - Diseases - Treatment (OCoLC)fst00847218 COVID-19 (Disease) - Treatment (OCoLC)fst01984645 Data integration (Computer science) (OCoLC)fst01763872 Medical care - Data processing (OCoLC)fst01013786 Christen, Nathaniel verfasserin aut 9780323851978 paperback 0323851975 paperback Erscheint auch als Druck-Ausgabe NEUSTEIN, AMY INNOVATIVE DATA INTEGRATION AND CONCEPTUAL SPACE MODELING FOR COVID, CANCER, AND CARDIAC CARE ELSEVIER ACADEMIC PRESS, 2022 0323851975 https://www.sciencedirect.com/science/book/9780323851978 X:ELSEVIER Verlag lizenzpflichtig BSZ-33-EBS-HSAA ZDB-33-ESD BSZ-33-ESD-L1FH ZDB-33-EGE 2022 GBV-33-EBS-HST BSZ-33-EBS-C1UB GBV_ILN_60 ISIL_DE-705 SYSFLAG_1 GBV_KXP GBV_ILN_132 ISIL_DE-959 GBV_ILN_185 ISIL_DE-Sra5 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2020 ISIL_DE-Ch1 GBV_ILN_2057 ISIL_DE-L189 GBV_ILN_2111 ISIL_DE-944 BO 045F 610.285 60 01 0705 450439636X 00 --%%-- --%%-- s --%%-- Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Nur für Angehörige der HSU: Volltextzugang von außerhalb des Campus mit Anmeldung über Shibboleth mit Ihrer Bibliothekskennung z 27-03-24 132 01 0959 4506287444 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. Zeitlich begrenzte Lizenzierung k 02-04-24 185 01 3519 4514771945 OLR-EBS Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 23-04-24 370 01 4370 4540288016 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2020 01 DE-Ch1 4520341329 00 --%%-- --%%-- n n Campuslizenz l01 03-05-24 2057 01 DE-L189 4467488618 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 2111 01 DE-944 4440938809 00 --%%-- E-Book Elsevier --%%-- n Elektronischer Volltext - Campuslizenz l01 19-12-23 60 01 0705 https://www.sciencedirect.com/science/book/9780323851978 132 01 0959 Zugriff nur für Angehörige der Hochschule Osnabrück im Hochschulnetz https://www.sciencedirect.com/science/book/9780323851978 185 01 3519 https://www.sciencedirect.com/science/book/9780323851978 370 01 4370 E-Book: Zugriff im HCU-Netz. 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Neustein, Amy 1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. misc R858 ddc 610.285 misc Medical care misc Data integration (Computer science) misc COVID-19 (Disease) misc Cancer misc Cardiovascular system misc Medical Informatics misc COVID-19 misc Neoplasms misc Cardiovascular Diseases misc Integration de donnees (Informatique) misc COVID-19 - Traitement misc Cancer - Traitement misc Appareil cardiovasculaire - Maladies - Traitement misc Soins medicaux - Informatique misc Medecine - Informatique misc Cancer - Treatment misc Cardiovascular system - Diseases - Treatment misc COVID-19 (Disease) - Treatment misc Medical care - Data processing 132 EBooks Elsevier Engineering Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care |
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1. Introduction -- 2. Data structures associated with biomedical research -- 3. Data mining and predictive analytics for cancer and COVID-19 -- 4. Modular design, image biomarkers, and radiomics -- 5. Types' internal structure and "non-constructive" ("NC4") type theory -- 6. Using code models to instantiate data models -- 7. Multi-aspect modules and image annotation -- 8. Image annotation as a multi-aspect case study -- 9. Conceptual spaces and scientific data models. |
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Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care Amy Neustein, Nathaniel Christen |
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Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care |
| abstract |
"In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Includes bibliographical references and index |
| abstractGer |
"In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Includes bibliographical references and index |
| abstract_unstemmed |
"In recent years, scientific research and translation medicine have placed increased emphasis on computational methodology and data curation across many disciplines, both to advance underlying science and to instantiate precision-medicine protocols in the lab and in clinical practice. The nexus of concerns related to oncology, cardiology, and virology (SARS-CoV-2) presents a fortuitous context within which to examine the theory and practice of biomedical data curation. Innovative Data Integration and Conceptual Space Modeling for COVID, Cancer, and Cardiac Care argues that a well-rounded approach to data modeling should optimally embrace multiple perspectives inasmuch as data-modeling is neither a purely formal nor a purely conceptual discipline, but rather a hybrid of both. On the one hand, data models are designed for use by computer software components, and are, consequently, constrained by the mechanistic demands of software environments; data modeling strategies must accept the formal rigors imposed by unambiguous data-sharing and query-evaluation logic. In particular, data models are not well-suited for software-level deployment if such models do not translate seamlessly to clear strategies for querying data and ensuring data integrity as information is moved across multiple points. On the other hand, data modeling is, likewise, constrained by human conceptual tendencies, because the information which is managed by databases and data networks is ultimately intended to be visualized/utilized by humans as the end-user."-- Includes bibliographical references and index |
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| title_short |
Innovative data integration and conceptual space modeling for COVID, cancer and cardiac care |
| url |
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