Software Open Access

Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models

Sibghat Ullah; Zhao Xu; Hao Wang; Stefan Menzel; Bernhard Sendhoff


JSON-LD (schema.org) Export

{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>This is the source code used in the following paper:</p>\n\n<p>Ullah, S., Xu, Z., Wang, H., Menzel, S., Sendhoff, B., &quot;Exploring Clinical Time Series Forecasting with Meta-Features in Variational Recurrent Models&quot;&nbsp;&nbsp;<em>2020 IEEE World Congress on Computational Intelligence&nbsp;</em></p>\n\n<p>This paper investigates the effectiveness of Supplementary Medical Information, for improving the prediction of Variational Recurrent Models in Clinical Time Series Forecasting. &nbsp;</p>", 
  "license": "https://opensource.org/licenses/GPL-3.0", 
  "creator": [
    {
      "affiliation": "University of Leiden", 
      "@id": "https://orcid.org/0000-0002-2627-6019", 
      "@type": "Person", 
      "name": "Sibghat Ullah"
    }, 
    {
      "affiliation": "NEC Laboratories GmBH", 
      "@type": "Person", 
      "name": "Zhao Xu"
    }, 
    {
      "affiliation": "University of Leiden", 
      "@id": "https://orcid.org/0000-0002-4933-5181", 
      "@type": "Person", 
      "name": "Hao Wang"
    }, 
    {
      "affiliation": "Honda Research Institute Europe GmBH", 
      "@type": "Person", 
      "name": "Stefan Menzel"
    }, 
    {
      "affiliation": "Honda Research Institute Europe GmBH", 
      "@id": "https://orcid.org/0000-0002-1233-9584", 
      "@type": "Person", 
      "name": "Bernhard Sendhoff"
    }
  ], 
  "url": "https://zenodo.org/record/3859741", 
  "datePublished": "2020-05-27", 
  "version": "1", 
  "@type": "SoftwareSourceCode", 
  "keywords": [
    "time series forecasting", 
    "recurrent neural networks", 
    "deep latent-variable models", 
    "MIMIC III", 
    "Clinical Applications"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.5281/zenodo.3859741", 
  "@id": "https://doi.org/10.5281/zenodo.3859741", 
  "workFeatured": {
    "url": "https://wcci2020.org/", 
    "alternateName": "IJCNN 2020", 
    "location": "Glasgow, UK", 
    "@type": "Event", 
    "name": "2020 IEEE World Congress on Computational Intelligence"
  }, 
  "name": "Exploring Clinical Time Series Forecasting with  Meta-Features in Variational Recurrent Models"
}
32
3
views
downloads
All versions This version
Views 3232
Downloads 33
Data volume 205.2 kB205.2 kB
Unique views 2626
Unique downloads 33

Share

Cite as