AI empowers traditional Chinese medicine to explore new potentials

(Xinhua) 09:35, March 29, 2024

BEIJING, March 29 (Xinhua) -- How can artificial intelligence (AI) impact on the traditional Chinese medicine (TCM), a practice spanning thousands of years, particularly at the grassroots level? This integration of TCM and AI has attracted increasing interest from hospitals, scholars and companies alike.

Seated in front of a desktop device, a person has a few photos of their face and tongue captured and then respond to five questions. Soon after, a comprehensive report detailing their specific physical conditions within the framework of TCM is readily available on their cellphone -- all thanks to AI.

In a community medical service center in Guangzhou, capital city of south China's Guangdong Province, many elderly residents who have used this AI equipment were impressed by the technology and the credible results.

An individual's personalized physical condition assessment, forming the cornerstone of tailored TCM diagnosis and treatment, constitutes a vital aspect of this practice.

China's National Standards for Basic Public Services (2023) stipulates that people over 65 years old should be provided with TCM physical condition appraisal and health care guidance at least once a year.

Previously, generating such a report took a longer duration, and many senior citizens found the process to be tedious and complicated, occasionally struggling to complete it.

They had to complete a form with 33 questions and it would take about 20 minutes as they needed to read and fill the form themselves or ask for help from the staff, said Han Yiyu, a physician at the center in the Shipai sub-district.

"Now with the newly installed AI equipment, the process only takes two minutes," said Yang Haiwen, deputy director of the center.

The equipment was developed by researchers from the South China University of Technology (SCUT) based on a machine-learning model. Following a series of training by TCM experts, the model can distinguish various diatheses and physical conditions from facial and tongue images, offering personalized health improvement advice accordingly.

In recent years, AI technologies and equipment such as AI prescription systems, acupuncture robots, and tui-na (massage) robots have increasingly penetrated TCM clinics.

Utilizing modern technologies, intelligent TCM products have narrowed the gap between people's growing demand for health care and the limited capacity of primary-level medical institutions.

Wu Jun, a researcher on the application of AI in TCM with the SCUT, has noticed an increasing interest in the TCM field in leveraging computer science and AI technology. "More people have seen the potential of AI, and they expect the technology to help promote TCM and enable it to play a greater role in primary-level health services," Wu said.

The application of AI might alleviate the shortage of experienced TCM professionals at primary-level institutions, especially in remote areas, said Wang Zhengfei, a researcher at the Guangzhou University of Chinese Medicine.

"With the assistance of AI, doctors at the primary level may obtain technical skills equivalent to experienced doctors and enhance their diagnostic accuracy. In this way, we can expect a broad application prospect of AI (in the TCM field)," Wang said.

While many are optimistic about AI's potential contribution to the modernization and advancement of TCM, several challenges still need to be addressed.

According to Wu, one major challenge is the standardization of TCM theories. There are different schools of TCM theories and they vary in diagnosis and treatment methods, posing challenges to product development and recognition.

Another challenge lies in the integration of TCM and technology. As AI relies on deep learning neural networks rather than predefined programs to generate results, medical professionals may question the results due to the challenge of accurately explaining the AI's working process.

Considering the challenges, the industry is striving to find solutions, Wu said.

(Web editor: Tian Yi, Liang Jun)


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