Narrative review of evaluation on the effect of traditional Chinese medicine on Alzheimer’s disease via machine learning approaches

Abstract

Alzheimer’s disease (AD), a chronic progressive neurodegenerative disorder without effective recovery treatment, is a major public health issue for the society with population ageing. The early treatment and care strategies may have a significant effect in delaying the progress of AD. Some evidence-based medicine research has found that a treatment strategy containing the combination of modern medicine and traditional Chinese medicine (TCM) may have advantages in AD to some extent. However, the current medical evidence may hardly evaluate the effect of TCM for AD with high confidence due to the low quality of related random control trials. Hence, to found a pipeline to evaluate the effect of TCM on AD more objectively, it is of interest to discuss how to use machine learning approaches to evaluate the effect of TCM for AD based on real-world data. For evaluating the effect of TCM for AD, this article gives a suggestion about a model that may be suitable to evaluate the effect of TCM for AD for different patients. And, this article will be divided into two parts. The first part will give a brief introduction to AD, TCM and machine learning. The second part will give the general suggestion about how to build the data set and evaluate the data. However, since AD is a complex disease, this review can only give a general suggestion for researches in this area and further consensus in details under censor between researchers is still needed.