A look at the recent oncology literature or a search of the common databases reveals a steadily increasing number of nomograms and other prognostic models. These models may predict the risk of relapse, lymphatic spread of a given malignancy, toxicity, survival, etc. Pathology information, gene signatures, and clinical data may all be used to compute the models. This trend reflects increasingly individualized treatment concepts, the need for approaches that achieve a favorable balance between effectiveness and side-effects, and the goal of optimal resource utilization reflecting prognostic knowledge. In order to avoid misuse, it is important to understand the limits and caveats of prognostic and predictive models. This book provides a comprehensive overview of such decision tools for radiation oncology, stratified by disease site, which will enable readers to make informed choices in daily clinical practice and to critically follow the future development of new tools in the field.>
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A look at the recent oncology literature or a search of one of the common databases reveals a steadily increasing number of nomograms and other prognostic models, some of which are also available in the form of web-based tools. These models may predict the risk of relapse, lymphatic spread of a given malignancy, toxicity, survival, etc. Pathology information, gene signatures, and clinical data may all be used to compute the models. This trend reflects increasingly individualized treatment concepts and also the need for approaches that achieve a favorable balance between effectiveness and side-effects. Moreover, optimal resource utilization requires prognostic knowledge, for example to avoid lengthy and aggressive treatment courses in patients with a short survival expectation. In order to avoid misuse, it is important to understand the limits and caveats of prognostic and predictive models. This book provides a comprehensive overview of such decision tools for radiation oncology, stratified by disease site, which will enable readers to make informed choices in daily clinical practice and to critically follow the future development of new tools in the field.
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Anbieter: Anybook.com, Lincoln, Vereinigtes Königreich
Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1200grams, ISBN:9783642371011. Bestandsnummer des Verkäufers 5777765
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Auflage: 2014. 305 Seiten sehr guter Zustand - innen sehr sauberes ungelesenes Ex. Äußerlich sind am Einband leichte Lagerspuren. 9783642371011 Sprache: Englisch Gewicht in Gramm: 1112 28,8 x 21,4 x 2,0 cm, Gebundene Ausgabe. Bestandsnummer des Verkäufers 81835
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Zustand: As New. Unread book in perfect condition. Bestandsnummer des Verkäufers 19968052
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Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Hardcover. Zustand: new. Hardcover. A look at the recent oncology literature or a search of the common databases reveals a steadily increasing number of nomograms and other prognostic models. These models may predict the risk of relapse, lymphatic spread of a given malignancy, toxicity, survival, etc. Pathology information, gene signatures, and clinical data may all be used to compute the models. This trend reflects increasingly individualized treatment concepts, the need for approaches that achieve a favorable balance between effectiveness and side-effects, and the goal of optimal resource utilization reflecting prognostic knowledge. In order to avoid misuse, it is important to understand the limits and caveats of prognostic and predictive models. This book provides a comprehensive overview of such decision tools for radiation oncology, stratified by disease site, which will enable readers to make informed choices in daily clinical practice and to critically follow the future development of new tools in the field.> A look at the recent oncology literature or a search of the common databases reveals a steadily increasing number of nomograms and other prognostic models. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9783642371011
Anbieter: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, Deutschland
Zustand: gut. 2014. Decision Tools for Radiation Oncology: Prognosis, Treatment Response and Toxicity Medical Radiology In deutscher Sprache. pages. Bestandsnummer des Verkäufers BN501210
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
Hardcover. Zustand: Brand New. 1st edition. 305 pages. 11.00x8.50x0.75 inches. In Stock. Bestandsnummer des Verkäufers x-3642371019
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Neuware - A look at the recent oncology literature or a search of the common databases reveals a steadily increasing number of nomograms and other prognostic models. These models may predict the risk of relapse, lymphatic spread of a given malignancy, toxicity, survival, etc. Pathology information, gene signatures, and clinical data may all be used to compute the models. This trend reflects increasingly individualized treatment concepts, the need for approaches that achieve a favorable balance between effectiveness and side-effects, and the goal of optimal resource utilization reflecting prognostic knowledge. In order to avoid misuse, it is important to understand the limits and caveats of prognostic and predictive models. This book provides a comprehensive overview of such decision tools for radiation oncology, stratified by disease site, which will enable readers to make informed choices in daily clinical practice and to critically follow the future development of new tools in the field.>. Bestandsnummer des Verkäufers 9783642371011
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