An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as An Example

Artificial intelligence is a modern technology that is utilized in various fields of medicine [1-3]. At the meantime, Chinese Traditional Medicine (TCM) is now widely considered as a promising alternative medicine for complementary treatment in cancers or chronic diseases due to the effective methodology practically developed by generations of doctors for almost 4000 years [4]. Based on previous verification, it is undeniable that there are many correlations between the TCM syndromes and western diseases, turning out novel approaches for enhancing the treatment efficiency and developing medicines regarding with TCM methodologies [5]. Unfortunately, hindered by the remarkable gap between the modern informatics and the fundament of TCM: antient Chinese philosophy, such correlations are still too elusive to be formulated precisely. Therefore, recently, in order to figure out the deep connection between modern science and TCM, the research combining TCM with AI for valid knowledge acquisition and mining attracts extremely attention, and hereby, leading to many profound works, such as ontology information system design [6], latent tree models design [7], TCM warehouse for AI application [8], and digital knowledge graph development [2]. On the other hand, researchers face, however, many difficulties in setting up AI for TCM in terms of directly interpreting TCM semantic system (almost recorded by ancient Chinese doctrines) into structured database. Because in this way, considerable workload must be undertaken by limited numbers of experts who are proficient in both AI and TCM to translate the TCM terminologies and then formulate the modern model thereof. In contrast, as shown in Figure 1, the digestion of using TCM methodology in dealing with issues of modern science, new medicine design for example, is relatively lacking and thus of significant worth to explore.