Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches

Daniel Stamate, Andrea Katrinecz, Daniel Stahl, Simone J. W. Verhagen, Philippe A. E. G. Delespaul, Jim van Os, Sinan Guloksuz*

*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Original languageEnglish
Pages (from-to)156-163
Number of pages8
JournalSchizophrenia Research
Volume209
DOIs
Publication statusPublished - Jul 2019

Keywords

  • Mobile health
  • Prediction
  • Schizophrenia
  • Smartphone
  • Computational psychiatry
  • Machine learning
  • MOMENTARY ASSESSMENT
  • RISK CALCULATOR
  • DAILY-LIFE
  • SCHIZOPHRENIA
  • INDIVIDUALS
  • STRESS
  • FEASIBILITY
  • PREDICTION
  • REACTIVITY
  • THERAPY

Cite this

Stamate, Daniel ; Katrinecz, Andrea ; Stahl, Daniel ; Verhagen, Simone J. W. ; Delespaul, Philippe A. E. G. ; van Os, Jim ; Guloksuz, Sinan. / Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches. In: Schizophrenia Research. 2019 ; Vol. 209. pp. 156-163.
@article{b474a91e75d749ee9423fde61726b6e1,
title = "Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches",
keywords = "Mobile health, Prediction, Schizophrenia, Smartphone, Computational psychiatry, Machine learning, MOMENTARY ASSESSMENT, RISK CALCULATOR, DAILY-LIFE, SCHIZOPHRENIA, INDIVIDUALS, STRESS, FEASIBILITY, PREDICTION, REACTIVITY, THERAPY",
author = "Daniel Stamate and Andrea Katrinecz and Daniel Stahl and Verhagen, {Simone J. W.} and Delespaul, {Philippe A. E. G.} and {van Os}, Jim and Sinan Guloksuz",
year = "2019",
month = "7",
doi = "10.1016/j.schres.2019.04.028",
language = "English",
volume = "209",
pages = "156--163",
journal = "Schizophrenia Research",
issn = "0920-9964",
publisher = "Elsevier Science",

}

Stamate, D, Katrinecz, A, Stahl, D, Verhagen, SJW, Delespaul, PAEG, van Os, J & Guloksuz, S 2019, 'Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches', Schizophrenia Research, vol. 209, pp. 156-163. https://doi.org/10.1016/j.schres.2019.04.028

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches. / Stamate, Daniel; Katrinecz, Andrea; Stahl, Daniel; Verhagen, Simone J. W.; Delespaul, Philippe A. E. G.; van Os, Jim; Guloksuz, Sinan.

In: Schizophrenia Research, Vol. 209, 07.2019, p. 156-163.

Research output: Contribution to journal › Article › Academic › peer-review

TY - JOUR

T1 - Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches

AU - Stamate, Daniel

AU - Katrinecz, Andrea

AU - Stahl, Daniel

AU - Verhagen, Simone J. W.

AU - Delespaul, Philippe A. E. G.

AU - van Os, Jim

AU - Guloksuz, Sinan

PY - 2019/7

Y1 - 2019/7

KW - Mobile health

KW - Prediction

KW - Schizophrenia

KW - Smartphone

KW - Computational psychiatry

KW - Machine learning

KW - MOMENTARY ASSESSMENT

KW - RISK CALCULATOR

KW - DAILY-LIFE

KW - SCHIZOPHRENIA

KW - INDIVIDUALS

KW - STRESS

KW - FEASIBILITY

KW - PREDICTION

KW - REACTIVITY

KW - THERAPY

U2 - 10.1016/j.schres.2019.04.028

DO - 10.1016/j.schres.2019.04.028

M3 - Article

VL - 209

SP - 156

EP - 163

JO - Schizophrenia Research

JF - Schizophrenia Research

SN - 0920-9964

ER -

Stamate D, Katrinecz A, Stahl D, Verhagen SJW, Delespaul PAEG, van Os J et al. Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches. Schizophrenia Research. 2019 Jul;209:156-163. https://doi.org/10.1016/j.schres.2019.04.028

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