Computational and Mathematical Methods in Medicine

Advances in Computational Psychometrics


Lead Editor

1Istituto Auxologico Italiano, Milan, Italy

2Telefónica I&D, Barcelona, Spain

3The Centre for Research and Technology, Hellas, Greece

4University in Wenzhou, Wenzhou, China

Advances in Computational Psychometrics


Computational and mathematical methods have been gaining a significant role in both medicine and psychology over past years. The mainstream in psychometrics is moving towards more profound analysis based on the technological and computational advancements as well as on more effective mathematical modeling. Moreover, emerging fields of affective and wearable computing are allowing for a deeper understanding of human psychology while new biomedical instruments are providing new dimension in the research domains related to medicine and psychology.

This special issue will have two foci, namely to feature works that advance scientific knowledge in the area of computational psychometrics and, on the other hand, deeply investigate methods, techniques and instruments for the assessment of cognitive, emotional and medical (diagnostics) mental health at the cutting edge of current technologies.

Potential topics include, but are not limited to:

  • Computational models of mental health and diseases
  • Psychometrics beyond reliability and validity
  • Affective computing for mental health and diseases
  • Wearable computing for the assessment and the rehabilitation of cognitive processes
  • Virtual reality and new interfaces for mental health
  • Human computer confluence
  • Advanced psychometric methods for early diagnosis of mental and neurological disorders
  • Technologies for monitoring (supporting) patients
  • Bioinformatics (including omics) and applications
  • Biological network modeling
  • Biosignal processing and analysis of psycho-physiological data
  • Agent-based models and applications to mental health
  • System dynamics and discrete event (rocess-centric) models for mental health
  • Statistical theories and models for advanced computational analysis in mental health
  • Survival analysis and quality-of-life issues
  • Comparative effectiveness research and patient-centered outcomes research

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