Visual analytics for the interpretation of fluency tests during Alzheimer evaluation

Antoine Lhuillier (1) , Christophe Hurter (2) , Christophe Jouffrais (3, 4) , Emmanuel J Barbeau (5) , Helene Amieva (6)

1 LII - ENAC - Equipe Informatique Interactive
2 ENAC - Ecole Nationale de l'Aviation Civile
3 IRIT-ELIPSE - Etude de L’Interaction Personne SystèmE
4 CNRS - Centre National de la Recherche Scientifique
5 CERCO - Centre de recherche cerveau et cognition
6 Epidemiologie-Biostatistique [Bordeaux]

A possible way to evaluate the progress of Alzheimer disease is to conduct the Isaac set test [13, 14]. In this activity, patients are asked to cite the largest possible number of city names within a minute. Since the city names are handwritten very quickly by a medical practitioner some cities are abbreviated or poorly written. In order to analyze such data, medical practitioners need to digitize the notes first and clean the dataset. Because these tasks are intricate and error prone we propose a novel set of tools, involving interactive visualization techniques, to help medical practitioners in the digitization and data-cleaning process. This system will be tested as part of an ongoing longitudinal study involving 9500 patients.

Mots clés: Data cleaning; Information Visualization; Electronic Health Records; 3C Dataset; Alzheimer Disease

Domaines: Informatique [cs]; Interface homme-machine [cs.HC]

Antoine Lhuillier, Christophe Hurter, Christophe Jouffrais, Emmanuel J Barbeau, Helene Amieva. Visual analytics for the interpretation of fluency tests during Alzheimer evaluation. VAHC '15 Workshop on Visual Analytics in Healthcare, Oct 2015, Chicago, United States. pp.ISBN:978-1-4503-3671-0, ⟨10.1145/2836034.2836037⟩. ⟨hal-01305917v2⟩