AI Article Synopsis
- The review examines how machine learning is being used in the research of acupuncture and moxibustion, focusing on prescription analysis, efficacy prediction, and the specificity of acupoints.
- It discusses current challenges faced in this area of research, such as data quality and model selection based on research goals.
- The text emphasizes the importance of designing effective features, prioritizing sample data collection, and creating standardized data sharing platforms to enhance future studies.
Article Abstract
The application progress of machine learning in research of acupuncture and moxibustion was reviewed from three aspects: mining of acupuncture and moxibustion prescription and indications, acupuncture efficacy prediction and its influencing factors, acupoint specificity and acupuncture manipulation research, and the existing problems in current research and future research trends were discussed. It is believed that the appropriate machine learning algorithm should be selected to build the model according to the research purpose and data characteristics in the future research; attention should be paid to feature design, feature selection and feature cleaning; sample data collection should be a priority, and data sharing platform and standardized data collection should be developed to improve the data quality.
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| http://dx.doi.org/10.13703/j.0255-2930.20191026-0002 | DOI Listing |
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