title: Posttraumatic stress disorder: diagnostic data analysis by data mining methodology.
abstract: OBJECTIVE
  To use data mining methods in assessing diagnostic symptoms in posttraumatic stress disorder (PTSD). METHODS. The study included 102 inpatients: 51 with a diagnosis of PTSD and 51 with psychiatric diagnoses other than PTSD. Several models for predicting diagnosis were built using the random forest classifier, one of the intelligent data analysis methods. The first prediction model was based on a structured psychiatric interview, the second on psychiatric scales (Clinician-administered PTSD Scale--CAPS, Positive and Negative Syndrome Scale--PANSS, Hamilton Anxiety Scale--HAMA, and Hamilton Depression Scale--HAMD), and the third on combined data from both sources. Additional models placing more weight on one of the classes (PTSD or non-PTSD) were trained, and prototypes representing subgroups in the classes constructed.
  
  
  RESULTS
  The first model was the most relevant for distinguishing PTSD diagnosis from comorbid diagnoses such as neurotic, stress-related, and somatoform disorders. The second model pointed out the scores obtained on the CAPS scale and additional PANSS scales, together with comorbid diagnoses of neurotic, stress-related, and somatoform disorders as most relevant. In the third model, psychiatric scales and the same group of comorbid diagnoses were found to be most relevant. Specialized models placing more weight on either the PTSD or non-PTSD class were able to better predict their targeted diagnoses at some expense of overall accuracy. Class subgroup prototypes mainly differed in values achieved on psychiatric scales and frequency of comorbid diagnoses.
  
  
  CONCLUSIONS
  Our work demonstrated the applicability of data mining methods for the analysis of structured psychiatric data for PTSD. In all models, the group of comorbid diagnoses, including neurotic, stress-related, and somatoform disorders, surfaced as important. The important attributes of the data, based on the structured psychiatric interview, were the current symptoms and conditions such as presence and degree of disability, hospitalizations, and duration of military service during the war, while CAPS total scores, symptoms of increased arousal, and PANSS additional criteria scores were indicated as relevant from the psychiatric symptom scales.
authors: Dubrava University Hospital, Department of Psychiatry, Referral Center of the Ministry of Health and Social Welfare for Stress-related Disorders, Zagreb, Croatia.
authors: Igor
authors: I
authors: Marinić
authors: Fran
authors: F
authors: Supek
authors: Zrnka
authors: Z
authors: Kovacić
authors: Lea
authors: L
authors: Rukavina
authors: Tihana
authors: T
authors: Jendricko
authors: Dragica
authors: D
authors: Kozarić-Kovacić
mesh_terms: D000328:Adult; D000465:Algorithms; D003625:Data Collection / Q000379:methods; D003627:Data Interpretation, Statistical; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D011581:Psychological Tests; D013313:Stress Disorders, Post-Traumatic / Q000145:classification / Q000175:diagnosis*