Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis

HIGHLIGHTS

  • who: Diogo F. Soares from the Universidade have published the research work: Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis, in the Journal: Scientific Reports Scientific Reports
  • what: The proposed predictors can straightforwardly combine static features with triclustering-based features (as the authors show at the end). Data were preprocessed in accordance with the approach proposed by Carreiro et_al12, which assumes the patients are followed up regularly and perform a normative set of tests after each appointment. The snapshots in which the patient is in a . . .

     

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