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Investigating data-driven biological subtypes of sychiatric disorders using specification-curve analysis.

Lian BeijersHanna M van LooJan-Willem RomeijnFemke LamersRobert A SchoeversKlaas J Wardenaar
Published in: Psychological medicine (2020)
SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients.
Keyphrases
  • end stage renal disease
  • ejection fraction
  • newly diagnosed
  • chronic kidney disease
  • peritoneal dialysis
  • air pollution
  • patient reported outcomes
  • machine learning
  • deep learning
  • data analysis
  • artificial intelligence