title: Software tool for improved prediction of Alzheimer's disease.
abstract: BACKGROUND
  Diagnostic criteria of Alzheimer's disease (AD) emphasize the integration of clinical data and biomarkers. In practice, collection and analysis of patient data vary greatly across different countries and clinics.
  
  
  OBJECTIVE
  The goal was to develop a versatile and objective clinical decision support system that could reduce diagnostic errors and highlight early predictors of AD.
  
  
  METHODS
  Novel data analysis methods were developed to derive composite disease indicators from heterogeneous patient data. Visualizations that communicate these findings were designed to help the interpretation. The methods were implemented with a software tool that is aimed for daily clinical practice.
  
  
  RESULTS
  With the tool, clinicians can analyze available patients as a whole, study them statistically against previously diagnosed cases, and characterize the patients with respect to having AD. The tool is able to work with virtually any patient measurement data, as long as they are stored in electronic format or manually entered into the system. For a subset of patients from the test cohort, the tool was able to predict conversion to AD at an accuracy of 93.6%.
  
  
  CONCLUSIONS
  The software tool developed in this study provides objective information for early detection and prediction of AD based on interpretable visualizations of patient data.
authors.affiliation: University of Eastern Finland, Kuopio University Hospital, Kuopio, Finland. hilkka.soininen@uef.fi
authors.forename: Hilkka
authors.initials: H
authors.lastname: Soininen
authors.forename: Jussi
authors.initials: J
authors.lastname: Mattila
authors.forename: Juha
authors.initials: J
authors.lastname: Koikkalainen
authors.forename: Mark
authors.initials: M
authors.lastname: van Gils
authors.forename: A
authors.initials: A
authors.lastname: Hviid Simonsen
authors.forename: Gunhild
authors.initials: G
authors.lastname: Waldemar
authors.forename: Daniel
authors.initials: D
authors.lastname: Rueckert
authors.forename: Lennart
authors.initials: L
authors.lastname: Thurfjell
authors.forename: Jyrki
authors.initials: J
authors.lastname: Lötjönen
mesh_terms: D000368:Aged; D000544:Alzheimer Disease / Q000175:diagnosis* / Q000209:etiology; D060825:Cognitive Dysfunction / Q000150:complications / Q000175:diagnosis*; D020000:Decision Support Systems, Clinical; D018450:Disease Progression; D005260:Female; D006801:Humans; D008137:Longitudinal Studies; D008297:Male; D011569:Psychiatric Status Rating Scales; D012984:Software