Kalya Research: Complementary and Alternative Medicine (CAM) Virtual Research Assistant from Biomedical Literature

Abstract

Complementary and alternative medicines (CAM) become an emerging subject of interest both for users and health professionals. Rigorous studies identify efficient and safe methods for human health, frequently called by researchers, non-pharmacological interventions. The challenge is to determine relevant articles in a large and increasing volume of publications and journals. To meet this challenge, we created Kalya Research (KR), a medical assistant tool based on artificial intelligence that selects and characterizes CAM literature and bring support to medical researchers. Based on rule models and ontologies, KR can suggest relevant and recent CAM publications. It presents key indicators through analytical visualizations. KR was evaluated at several points (effectiveness, relevance, usability) in 2 ways, by means of a bibliographic search comparison with MedLine and by questioning more than 40 biomedical researchers who used KR for their research. When compared with Medline, KR highlighted most of the relevant CAM publications. The evaluation by the researchers showed that the majority of them found the tool to be relevant and time saver and feature-rich. Our future objectives are therefore to constantly develop the application to improve our models for detecting CAM publications and named entities (diseases, CAMs, outcomes), and to extend it to new health topics.