Literature DB >> 21797513

Statistical validation of event predictors: a comparative study based on the field of seizure prediction.

Hinnerk Feldwisch-Drentrup1, Andreas Schulze-Bonhage, Jens Timmer, Björn Schelter.   

Abstract

The prediction of events is of substantial interest in many research areas. To evaluate the performance of prediction methods, the statistical validation of these methods is of utmost importance. Here, we compare an analytical validation method to numerical approaches that are based on Monte Carlo simulations. The comparison is performed in the field of the prediction of epileptic seizures. In contrast to the analytical validation method, we found that for numerical validation methods insufficient but realistic sample sizes can lead to invalid high rates of false positive conclusions. Hence we outline necessary preconditions for sound statistical tests on above chance predictions.

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Year:  2011        PMID: 21797513     DOI: 10.1103/PhysRevE.83.066704

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  3 in total

1.  Prediction of Seizure Recurrence. A Note of Caution.

Authors:  William J Bosl; Alan Leviton; Tobias Loddenkemper
Journal:  Front Neurol       Date:  2021-05-13       Impact factor: 4.003

2.  Technical considerations for evaluating clinical prediction indices: a case study for predicting code blue events with MEWS.

Authors:  Kais Gadhoumi; Alex Beltran; Christopher G Scully; Ran Xiao; David O Nahmias; Xiao Hu
Journal:  Physiol Meas       Date:  2021-06-17       Impact factor: 2.688

3.  Ngram-derived pattern recognition for the detection and prediction of epileptic seizures.

Authors:  Amir Eftekhar; Walid Juffali; Jamil El-Imad; Timothy G Constandinou; Christofer Toumazou
Journal:  PLoS One       Date:  2014-06-02       Impact factor: 3.240

  3 in total

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