CLITA: Discovering Knowledge from Clinical Data

Abstract

Healthcare organizations manage patient’s disease relevant information in a systemic way, which could be utilized for the purpose of relational analysis. The open issue in the clinical data is its sparseness, which makes it difficult to analyze manually. Data mining techniques are greatly adopted to cope with this problem. This research proposes an approach named as CLITA (Clinical Treatment Analysis) for transforming raw clinical data into meaningful information. In particular, the aim of this study is to analyze the complaints registered by the patients and their diagnosis carried out by the medical experts. CLITA exploits well-established data mining techniques (i.e., sequential pattern mining and association analysis) to transform real clinical data into knowledge. The discovered knowledge is evaluated and validated by the medical experts. The experts of the healthcare services may seek and utilize this knowledge for providing the treatment to patients and make the process more effective and purposeful.