TABLE 4.

Application of AI in TCM industry technology.

Aim of study	AI methods	Results	REF
Study the value of tongue picture and tongue coating microflora in the diagnosis of gastric cancer	Deep learning	Developed three artificial intelligence deep learning diagnosis models based on tongue images	Yuan et al. (2023)
Propose an artificial intelligence (AI) system for diagnosis of congenital heart diseases	Computed tomography images, deep learning	Proved the potential of our model to be integrated into current clinic practice to improve the diagnosis of CHD globally	Xu et al. (2023b)
Introduce an automated tool -computer-assisted cardiac cavity tracking (CACCT) to identify complicated cardiac malformations in mouse hearts	Deep learning	CACCT can identify complicated cardiac malformations in mouse hearts automatically	Chu et al. (2020)
report a clinically applicable system to detect gastric cancer	Deep convolutional neural network	The system could aid pathologists in improving diagnostic accuracy	Song et al. (2020)
Propose a graph based multichannel feature fusion (GBMFF) method for wrist pulse diagnosis	Graph convolutional networks	Demonstrated the proposed AI-based method can obtain great performances	Zhang et al. (2021b)
Assist diagnosis of tongue images and realize intelligent tongue diagnosis	U-Net with Global Convolution Network Module	Proposed an improved U-Net network which has a better segmentation effect and higher segmentation accuracy for fissured tongue image dataset	Li et al. (2021)
Construct tongue coating recognition model to assist syndrome diagnosis	Convolutional neural network technique, greasy tongue coating recognition networks (GreasyCoatNet)	Derived a disease-specific deep learning network by finetuning the generic GreasyCoatNet	Wang et al. (2022e)
Construction of Chinese herbal prescriptions from tongue images	Deep learning, CNNs	Verified the feasibility of the proposed method for the automatic construction of herbal prescriptions from tongue images	Hu et al. (2021)
Developed an SPL analysis system for wide-field images	Deep convolutional neural networks (DCNNs)	The method can achieve dermatologist-level detection of suspicious pigmented skin lesions	Soenksen et al. (2021)
Develop an artificial intelligence network to simulate the clinical decision-making of radiotherapy	3D convolutional neural network	Proved the feasibility of artificial intelligence in predicting the dose prescription of CDM radiotherapy	Cao et al. (2023)
Opens an avenue for mental health and evaluates the impact of therapeutic interventions to enhance a holistic state of health	Decision Tree Algorithms, machine learning	Offered a unique approach to characterizing health issues related to psychosomatic health	Morande (2022)
Enhance the explainability of AI applications in healthcare for hospital recommendation	Deep learning, decision trees	Improved the explainability of AI applications in healthcare	Wang et al. (2023c)
Summarize the application of AI in healthcare sector	Machine learning	Although AI holds significant potential for improving patient care, it also presents risks and challenges	Polevikov (2023)