Literature-based discovery approaches for evidence-based healthcare: a systematic review

Literature-Based Discovery (LBD) is a text mining technique used to generate novel hypotheses from vast amounts of literature sources, by identifying links between concepts from disparate sources. One of the main areas where it has been predominantly applied is the healthcare domain, whereby promising results, in the form of novel hypotheses, have been reported. The purpose of this work was to conduct a systematic literature review of recent publications on LBD in the healthcare domain in order to assess the trends in the approaches used and to identify issues and challenges for such systems.

The review was conducted following the principles of the Kitchenham method. The selected studies have been scrutinized and the derived findings have been reported following the PRISMA guidelines.

The review results reveal useful information regarding the application areas, the data sources considered, the approaches used, the performance in terms of accuracy and reliability and future research challenges. The results of this review will be beneficial to LBD researchers and other stakeholders in the healthcare domain, by providing them with useful insights on the approaches to adopt, data sources to consider, evaluation model to use and challenges to reflect on.

The synthesis of the results of this work has shed light on recent issues and challenges that drive new LBD models and provides avenues for their application in other diverse areas in the healthcare domain. To the best of our knowledge, no such recent review has been conducted.