Traditional Chinese Medicine with Data Visualization: Prospects and Difficulties in the Age of Big Data

Abstract

With the advent of personal computers, the Internet, portable devices, and big data analytical settings, computer-based medical diagnostic technologies have grown substantially since the 1950s. To address difficult issues related to health and illness, these technologies use the rudiments of information retrieval and representation (IRR). But, these systems have, from the beginning, paid little attention to TCM methods, often because these approaches have failed in randomized controlled studies. There is still a lot of mystery around traditional Chinese medicine (TCM), despite the fact that it is an integral aspect of healthcare systems across the globe, especially in a number of Asian nations. In view of current IRR techniques, it would be beneficial to compare traditional Chinese medicine (TCM) diagnostic and treatment methods with Western medical models in order to find out whether a new kind of translational medicine can be created that improves medical outcomes while lowering health care costs globally. This would be necessary because disease is still prevalent in society. Using bibliometric tools, multiple correspondence analysis, and data visualizations, this study examines author productivity, collaborations, and research trends in TCM and IRR published in SCOPUS from 1985 to 2020. As we embark on a new age of data-intensive scientific discovery in medicine, opportunities and difficulties have been identified that will help us determine the field's future courses.