VoQs: A Web Application for Visualization of Questionnaire Surveys

• Published in: Advances in Intelligent Data Analysis XIV Vol. 9385; pp. 334 - 343
• Main Authors: Zhang, Xiaowei, Klawonn, Frank, Grigull, Lorenz, Lechner, Werner
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 01.01.2015; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Amyotrophic Lateral Sclerosis; Answer Pattern; Artificial intelligence; Image processing; Neuromuscular Disease; Orphan Disease; Pattern recognition; Sequence Logo
• ISBN: 3319244647; 9783319244648
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-24465-5_29

This paper is motivated by analyzing questionnaire data that collected from patients who suffer from an orphan disease. In order to decrease misdiagnoses and shorten the diagnosis time for people who have not been diagnosed yet but already have a long history of health problems, a research project about using questionnaire mode and data analysis methods to predetermine orphan disease has been set up and questionnaires were designed based on experiences from patients who already have a diagnosis. The main focus of this work is to visualize answering patterns that characterize patients with a specific orphan disease, which questions are most useful to distinguish between certain orphan diseases and how well an answering pattern of a specific patient fits to the general pattern of those patients who share the same disease. We borrow from the concept of sequence logos, commonly used in genetics to visualize the conservation of nucleotides in a strand of DNA or RNA. Instead of nucleotides, we have possible answers from a question. Our proposed visualization techniques are not limited to questionnaires on orphan diseases but also can be applied to any questionnaire survey with closed-ended questions for which we are interested in answering characteristics of different groups.