A Recommender System to Help Discovering Cohorts in Rare Diseases

摘要

Cohort studies have been playing a key role in helping our understanding of diseases, health conditions, and treatments. These cohorts are often composed of a small number of subjects, especially in rare diseases studies, which reduces the statistical power of the results. One solution that can strengthen the scientific findings is to combine distinct studies and perform then multi-cohort analysis. However, even studies conducted for the same purpose in distinct research groups can have different scopes and medical observations, which preclude across-cohort exploration. In this paper, we propose a recommendation system to automatically discover cohorts of interest. This methodology uses context-based retrieval techniques combined with collaborative filtering to find relevant cohorts and scientific literature about a specific clinical investigation. The system was validated in a community focused on the study of Alzheimer's diseases, which includes 62 cohorts.