ReviewFrontiers in medicine2025
Application of artificial intelligence-assisted Traditional Chinese medicine formula granules in bone and joint degenerative diseases in the field of holistic health.
Review in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 3 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
3 citing papers in PubMed.
- Intelligent data governance and quality control for chest Bi syndrome/coronary heart disease across the prevention-treatment-rehabilitation continuum: integrating a standardized framework, adversarially-optimized trigger engine, and domain-adaptive AI.Frontiers in medical technology · 2026Article
- Artificial Intelligence in Traditional Chinese Medicine: Unraveling Herbal Medicine's Mechanisms.Research (Washington, D.C.) · 2026Review
- Efficacy and Safety Comparisons of Lingshu Granule versus Decoction in Polycystic Ovary Syndrome Patients with Insulin Resistance: A Multicenter Randomized Controlled Dose-Finding Trial Protocol.International journal of women's health · 2025Article
Corrections and comments
- Retraction · 2026-01-26Compromised Peer Review · Concerns/Issues about Data · Concerns/Issues about Methods · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Results and/or Conclusions · Investigation by Journal/Publisher · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As global aging intensifies, the incidence of degenerative bone and joint diseases such as osteoarthritis bone aging and osteoporosis continues to rise. Traditional treatment methods face bottlenecks in long-term management, including drug side effects and low patient compliance. Traditional Chinese medicine (TCM) formula granules, which utilize plant-based natural products, show excellent clinical efficacy in managing these conditions. With the development of technology, artificial intelligence (AI) technology has enhanced the clinical efficacy of TCM formula granules through multiple approaches such as intelligent syndrome differentiation and formula optimization, drug efficacy prediction and mechanism analysis, as well as patient management and therapeutic effect monitoring, providing a new approach for the prevention and treatment of complex degenerative diseases. This paper systematically reviews the core advantages of TCM formula granules and their suitability for orthopedic diseases such as bone aging and osteoporosis. It analyzes the application models of AI technology in optimizing TCM formula granules, predicting drug efficacy, and personalized treatment. The main research results show that the artificial intelligence-driven TCM formula granule system is beneficial for promoting the full-cycle integration of "prevention - treatment - rehabilitation" in the chronic disease management of bone and joint degenerative diseases. However, challenges persist in clinical evidence standardization, algorithm interpretability, and ethical frameworks. Future directions require interdisciplinary technological innovation, policy-industrial synergy, and global collaboration to advance intelligent TCM transformation for degenerative disease management.
Indexed as
Identifiers
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.