From data to diagnosis: A logical learning method to enhance interpretability in bipolar and major depressive disorder identification

This publication has 46 references indexed in Scilit:

• Metabolomic Biomarker Signatures for Bipolar and Unipolar Depression
  JAMA Psychiatry, 2024
• Deep Learning for Cross-Diagnostic Prediction of Mental Disorder Diagnosis and Prognosis Using Danish Nationwide Register and Genetic Data
  JAMA Psychiatry, 2023
• Integrating proteomic and clinical data to discriminate major psychiatric disorders: Applications for major depressive disorder, bipolar disorder, and schizophrenia
  Clinical and Translational Medicine, 2022
• Shared and Specific Patterns of Structural Brain Connectivity Across Affective and Psychotic Disorders
  Biological Psychiatry, 2022
• Learning the parameters of an outranking-based sorting model with characteristic class profiles from large sets of assignment examples
  Applied Soft Computing, 2022
• Resting state functional network switching rate is differently altered in bipolar disorder and major depressive disorder
  Human Brain Mapping, 2020
• Brain Morphometric Biomarkers Distinguishing Unipolar and Bipolar Depression
  JAMA Psychiatry, 2014
• Robust ordinal regression in preference learning and ranking
  Machine Learning, 2013
• Learning monotone nonlinear models using the Choquet integral
  Machine Learning, 2012
• The concept of a linguistic variable and its application to approximate reasoning—I
  Information Sciences, 1975