Development and Application of Traditional Chinese Medicine Using AI Machine Learning and Deep Learning Strategies

Area of Science:

• Integrative medicine
• Computational biology
• Medical informatics

Background:

• Traditional Chinese Medicine (TCM) offers effective treatments for complex illnesses with minimal side effects.
• TCM's advancement is hindered by a lack of objective standards for its abstract diagnostic methods and theories.
• Emerging technologies like machine learning (ML) and deep learning (DL) present opportunities to modernize TCM.

Purpose of the Study:

• To review the application and integration of ML and DL in Traditional Chinese Medicine.
• To highlight practical examples and discuss the achievements, challenges, and future potential of ML/DL in TCM.

Main Methods:

• Overview of ML and DL methodologies applied to TCM.
• Analysis of practical applications in TCM diagnostics and treatment.
• Discussion of integration successes and challenges.

Main Results:

• ML and DL are being successfully applied in TCM areas like tongue and pulse diagnosis.
• These technologies offer novel ways to explore TCM's theoretical framework.
• Early successes demonstrate the potential for objective standardization in TCM.

Conclusions:

• ML and DL integration is advancing TCM by providing objective standards.
• Continued evolution of ML/DL techniques promises further innovation in TCM.
• Addressing current challenges will unlock the full potential of AI-powered TCM.