ReviewFrontiers in pharmacology2024
Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review.
Review in Frontiers in pharmacology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
34 citing papers in PubMed.
- Risk of bias among Chinese-language randomized controlled trials on Chinese herbal medicine included in meta-analyses published in 2021-2022: A cross-sectional study.Integrative medicine research · 2026Article
- Integrative Medicine for Liver Fibrosis: Bioactive Constituents and Therapeutic Potential of Scutellaria baicalensis.Chinese journal of integrative medicine · 2026Review
- Beyond transparency: why Traditional Chinese Medicine (TCM) need explainable artificial intelligence (XAI).Chinese medicine · 2026Review
- Machine Learning-Aided Drug Repurposing for Screening COX-2 Inhibitors from Traditional Chinese Medicines.Pharmaceuticals (Basel, Switzerland) · 2026Article
- Future prospects of antiviral research in traditional Chinese medicine.Chinese herbal medicines · 2026Review
- Regulatory mechanisms of Traditional Chinese Medicine on gut microbiota in diabetic microvascular complications.Chinese medicine · 2026Review
- Rethinking Nature's Pharmacy: AI Era and Natural Product Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Traditional Chinese Medicine Modernization in Diagnosis and Treatment: Utilizing Artificial Intelligence and Nanotechnology.MedComm · 2026Review
- Advancing the modernization of traditional Chinese medicine through artificial intelligence and multimodal data integration.Chinese medicine · 2026Review
- Development and application of artificial intelligence in traditional Chinese medicine research and development.Chinese medicine · 2026Review
- Investigating the impact of dual-chain coupling on new quality productive forces in leading traditional Chinese medicine enterprises.Frontiers in medicine · 2026Article
- Metabolomics-Driven Precision Prevention and Treatment of Heart Failure with Traditional Chinese Medicine: From Mechanistic Insights to Metabolic Network Regulation.Drug design, development and therapy · 2026Review
- Artificial Intelligence in Traditional Chinese Medicine: Unraveling Herbal Medicine's Mechanisms.Research (Washington, D.C.) · 2026Review
- Should the Workload of Combining Clinical Practice With Data Collection be Considered: A Survey of Physicians With Data Collection Experience.Journal of evidence-based medicine · 2025Article
- Artificial intelligence in traditional medicine: policy and governance strategies.Bulletin of the World Health Organization · 2025Article
- The integration of machine learning into traditional Chinese medicine.Journal of pharmaceutical analysis · 2025Review
- [Analysis of the global registration status of clinical trials for artificial intelligence medical device].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Article
- Traditional Chinese medicine as a promising choice for future control of PEDV.Virus research · 2025Review
- A review of recent artificial intelligence for traditional medicine.Journal of traditional and complementary medicine · 2025Review
- Therapeutic potential and pharmacological mechanisms of Traditional Chinese Medicine in gout treatment.Acta pharmacologica Sinica · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.