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Artificial Intelligence in Medicine [electronic resource] : 15th Conference on Artificial Intelligence in Medicine, AIME 2015, Pavia, Italy, June 17-20, 2015. Proceedings / edited by John H. Holmes, Riccardo Bellazzi, Lucia Sacchi, Niels Peek.

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 9105 | Lecture Notes in Computer Science ; 9105Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XVI, 345 p. 76 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319195513
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
Online resources:
Contents:
Process mining and phenotyping -- Data mining and machine learning -- Temporal data mining -- Uncertainty and Bayesian networks -- Text mining -- Prediction in clinical practice.- Knowledge representation and guidelines.
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 15th Conference on Artificial Intelligence in Medicine, AIME 2015, held in Pavia, Italy, in June 2015. The 19 revised full and 24 short papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: process mining and phenotyping; data mining and machine learning; temporal data mining; uncertainty and Bayesian networks; text mining; prediction in clinical practice; and knowledge representation and guidelines.
Item type: E-BOOKS
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Process mining and phenotyping -- Data mining and machine learning -- Temporal data mining -- Uncertainty and Bayesian networks -- Text mining -- Prediction in clinical practice.- Knowledge representation and guidelines.

This book constitutes the refereed proceedings of the 15th Conference on Artificial Intelligence in Medicine, AIME 2015, held in Pavia, Italy, in June 2015. The 19 revised full and 24 short papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: process mining and phenotyping; data mining and machine learning; temporal data mining; uncertainty and Bayesian networks; text mining; prediction in clinical practice; and knowledge representation and guidelines.

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The Institute of Mathematical Sciences, Chennai, India