# Artificial intelligence in acupuncture: bridging traditional knowledge and precision integrative medicine

**Authors:** Guo-Liang Hou, Bao-Qiang Dong, Ben-Xing Yu, Jian-Yu Dai, Xing-Xing Lin, Ze-Zhong Cheng

PMC · DOI: 10.3389/fmed.2025.1633416 · 2025-07-31

## TL;DR

This paper explores how AI is transforming acupuncture from a traditional practice into a data-driven, precision medicine approach.

## Contribution

The paper reviews recent AI techniques in acupuncture and outlines future directions for improving data integration and clinical validation.

## Key findings

- AI techniques like CNNs and NLP are improving diagnostic objectivity and treatment planning in acupuncture.
- Current AI applications in acupuncture face challenges due to limited and inconsistent datasets.
- Federated data platforms and explainable AI are recommended to advance the field.

## Abstract

The integration of artificial intelligence (AI) into acupuncture research is accelerating the transformation of this traditional, experience-based practice into a data-driven, precision discipline. This review synthesizes recent advances in AI-enabled outcome prediction techniques, encompassing deep learning, meta-analytic modeling, natural language processing (NLP), computer vision, and neuroimaging-based analysis. For instance, convolutional neural networks (CNNs) have been successfully applied to classify tongue images and detect ZHENG patterns, while transformer-based NLP models enable automated extraction of clinical knowledge from classical texts. These technologies improve diagnostic objectivity, standardize treatment planning, and facilitate individualized care by enabling longitudinal efficacy modeling and real-time monitoring. Despite their potential, current implementations are constrained by limited and heterogeneous datasets, annotation variability, and gaps in clinical validation. We analyze key methodological innovations and challenges, and recommend future directions including the construction of federated multimodal data platforms, development of explainable AI frameworks, and promotion of open science practices. This convergence of AI and acupuncture presents a unique opportunity to enhance scientific rigor, clinical utility, and global integration of acupuncture within the paradigm of precision integrative medicine.

## Full-text entities

- **Diseases:** hallucination (MESH:D006212), gastrointestinal disorders (MESH:D005767), chronic pain (MESH:D059350), depression (MESH:D003866), migraine (MESH:D008881), FD (MESH:D004415), pain (MESH:D010146), insomnia (MESH:D007319), neurological and psychiatric disorders (MESH:D001523)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

1 figure with captions in the complete paper: https://tomesphere.com/paper/PMC12350448/full.md

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Source: https://tomesphere.com/paper/PMC12350448