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Applying machine learning on health record data from general practitioners to predict suicidality.
van Mens, Kasper; Elzinga, Elke; Nielen, Mark; Lokkerbol, Joran; Poortvliet, Rune; Donker, Gé; Heins, Marianne; Korevaar, Joke; Dückers, Michel; Aussems, Claire; Helbich, Marco; Tiemens, Bea; Gilissen, Renske; Beekman, Aartjan; de Beurs, Derek.
Affiliation
  • van Mens K; Altrecht Mental Healthcare, Utrecht, the Netherlands.
  • Elzinga E; Trimbos Institute (Netherlands Institute of Mental Health), Utrecht, the Netherlands.
  • Nielen M; 113 Suicide Prevention, Amsterdam, the Netherlands.
  • Lokkerbol J; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Poortvliet R; Trimbos Institute (Netherlands Institute of Mental Health), Utrecht, the Netherlands.
  • Donker G; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Heins M; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Korevaar J; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Dückers M; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Aussems C; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Helbich M; Nivel, Netherlands Institute for Health Services Research, Utrecht, the Netherlands.
  • Tiemens B; Human Geography and Spatial Planning, Utrecht University, Utrecht, the Netherlands.
  • Gilissen R; Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands.
  • Beekman A; 113 Suicide Prevention, Amsterdam, the Netherlands.
  • de Beurs D; Psychiatry, Amsterdam Public Health (research institute), Amsterdam UMC, Vrije Universiteit Amsterdam, the Netherlands.
Internet Interv ; 21: 100337, 2020 Sep.
Article in En | MEDLINE | ID: mdl-32944503
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Internet Interv Year: 2020 Document type: Article Affiliation country: Country of publication:
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Observational_studies / Prognostic_studies / Risk_factors_studies Language: En Journal: Internet Interv Year: 2020 Document type: Article Affiliation country: Country of publication: