Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis | Zendy

Stefan Dietrich | Zendy; Anna Floegel | Zendy; Martina Troll | Zendy; Tilman Kühn | Zendy; Wolfgang Rathmann | Zendy; Annette Peters | Zendy; Disorn Sookthai | Zendy; Martin von Bergen� | Zendy; Rudolf Kaaks | Zendy; Jerzy Adamski | Zendy; Cornelia Prehn | Zendy; Heiner Boeing | Zendy; Matthias B. Schulze | Zendy; Thomas Illig | Zendy; Tobias Pischon | Zendy; Sven Knüppel | Zendy; Rui WangSattler | Zendy; Dagmar Drogan | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Random Survival Forest in practice: a method for modelling complex metabolomics data in time to event analysis

Author(s) -

Stefan Dietrich,

Anna Floegel,

Martina Troll,

Tilman Kühn,

Wolfgang Rathmann,

Annette Peters,

Disorn Sookthai,

Martin von Bergen�,

Rudolf Kaaks,

Jerzy Adamski,

Cornelia Prehn,

Heiner Boeing,

Matthias B. Schulze,

Thomas Illig,

Tobias Pischon,

Sven Knüppel,

Rui WangSattler,

Dagmar Drogan

Publication year - 2016

Publication title -

international journal of epidemiology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.406

H-Index - 208

eISSN - 1464-3685

pISSN - 0300-5771

DOI - 10.1093/ije/dyw145

Subject(s) - proportional hazards model , european prospective investigation into cancer and nutrition , regression , random forest , regression analysis , multicollinearity , feature selection , statistics , medicine , prospective cohort study , computer science , oncology , data mining , mathematics , machine learning

The application of metabolomics in prospective cohort studies is statistically challenging. Given the importance of appropriate statistical methods for selection of disease-associated metabolites in highly correlated complex data, we combined random survival forest (RSF) with an automated backward elimination procedure that addresses such issues.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research