Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 16th International M Paolo Cazzaniga,Daniela Besozzi,Luca Manzoni

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Aviary

0302-9743 s and Biostatistics, CIBB 2019, which was held in Bergamo, Italy, during September 4-6, 2019. ..The 28 full papers presented in this volume were carefully reviewed and selected from 55 submissions. The papers are grouped in topical sections as follows: Computational Intelligence Methods for Bioinfor

Cubicle

0302-9743 cine; Machine Learning in Healthcare Informatics and Medical Biology; Modeling and Simulation Methods for Computational Biology and Systems Medicine..978-3-030-63060-7978-3-030-63061-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Stochastische Differentialgleichungen,uclear norm penalization for learning drug sensitivity. Numerical results show that the composite low-rank structure can improve the prediction performance compared to using a global low-rank approach or elastic net regression.

跟隨

Asymptotik integrierter Prozesses in terms of classification accuracy. Although not superior to 1-nearest neighbor (1-NN) and dynamic time warping (DTW), it has interesting characteristics for some classes, and thus enriches the set of methods to analyze multivariate TS.

Alienated

Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank uclear norm penalization for learning drug sensitivity. Numerical results show that the composite low-rank structure can improve the prediction performance compared to using a global low-rank approach or elastic net regression.

insipid

MSAX: Multivariate Symbolic Aggregate Approximation for Time Series Classifications in terms of classification accuracy. Although not superior to 1-nearest neighbor (1-NN) and dynamic time warping (DTW), it has interesting characteristics for some classes, and thus enriches the set of methods to analyze multivariate TS.

Indent

Funktionaldichten und Stereologie,om Essential Tremor without the use of more subjective questionnaires. This study shows that tremor data gathered using the TREMOR12 application is useful for constructing machine learning models that can be used to support the diagnosis and monitoring of patients who suffer from Essential Tremor.

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