Medical Risk Prediction Models: With Ties to Machine Learning (The Chapman & Hall/CRC Biostatistics) - Softcover

Buch 115 von 151: Chapman & Hall/CRC Biostatistics

Gerds, Thomas A.; Kattan, Michael W.

 
9780367673734: Medical Risk Prediction Models: With Ties to Machine Learning (The Chapman & Hall/CRC Biostatistics)
Softcover
ISBN 10: 0367673738 ISBN 13: 9780367673734
Verlag: Chapman and Hall/CRC, 2022

Inhaltsangabe

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.

Features:

    • All you need to know to correctly make an online risk calculator from scratch.
    • Discrimination, calibration, and predictive performance with censored data and competing risks.
    • R-code and illustrative examples.
    • Interpretation of prediction performance via benchmarks.
    • Comparison and combination of rival modeling strategies via cross-validation.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

Thomas A. Gerds is professor at the biostatistics unit at the University of Copenhagen. He is affiliated with the Danish Heart Foundation. He is author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years.

Michael Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision Making Research.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Chapman and Hall/CRC
Erscheinungsdatum
2022
Sprache
Englisch
ISBN 10 
0367673738
ISBN 13 
9780367673734
Einband
Taschenbuch
Auflage
1
Anzahl der Seiten
312
Kontakt zum Hersteller
Nicht verfügbar
Verantwortliche Person
Nicht verfügbar

Weitere beliebte Ausgaben desselben Titels

9781138384477: Medical Risk Prediction Models: With Ties to Machine Learning (Chapman & Hall/CRC Biostatistics)

Vorgestellte Ausgabe

ISBN 10:  113838447X ISBN 13:  9781138384477
Verlag: Chapman and Hall/CRC, 2021
Hardcover