ReviewEvidence-based complementary and alternative medicine : eCAM2015
Advances in Patient Classification for Traditional Chinese Medicine: A Machine Learning Perspective.
Review in Evidence-based complementary and alternative medicine : eCAM, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
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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.
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Who cites it
24 citing papers in PubMed, 90 citations in OpenAlex.
- Tuning and clinical application of large language models in Traditional Chinese Medicine: scoping review.Chinese medicine · 2026Review
- Advancing the modernization of traditional Chinese medicine through artificial intelligence and multimodal data integration.Chinese medicine · 2026Review
- Artificial Intelligence in Oral Diagnosis: Detecting Coated Tongue with Convolutional Neural Networks.Diagnostics (Basel, Switzerland) · 2025Article
- Construction and Application of a Traditional Chinese Medicine Syndrome Differentiation Model for Dysmenorrhea Based on Machine Learning.Combinatorial chemistry & high throughput screening · 2025Article
- Digital intelligence technology: new quality productivity for precision traditional Chinese medicine.Frontiers in pharmacology · 2025Review
- The Astragalus Membranaceus Herb Attenuates Leukemia by Inhibiting the FLI1 Oncogene and Enhancing Anti-Tumor Immunity.International journal of molecular sciences · 2024Article
- Predicting TCM patterns in PCOS patients: An exploration of feature selection methods and multi-label machine learning models.Heliyon · 2024Article
- Machine Learning Research Trends in Traditional Chinese Medicine: A Bibliometric Review.International journal of general medicine · 2024Review
- Machine learning in TCM with natural products and molecules: current status and future perspectives.Chinese medicine · 2023Review
- Article
- Towards Generating Realistic Wrist Pulse Signals Using Enhanced One Dimensional Wasserstein GAN.Sensors (Basel, Switzerland) · 2023Article
- Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review.Frontiers in pharmacology · 2023Review
- Objective evaluation of tongue diagnosis ability using a tongue diagnosis e-learning/e-assessment system based on a standardized tongue image database.Frontiers in medical technology · 2023Article
- Deep autoencoder-powered pattern identification of sleep disturbance using multi-site cross-sectional survey data.Frontiers in medicine · 2022Article
- Refined Multiscale Entropy Analysis of Wrist Pulse for Gender Difference in Traditional Chinese Medicine among Young Individuals.Evidence-based complementary and alternative medicine : eCAM · 2022Article
- Research of insomnia on traditional Chinese medicine diagnosis and treatment based on machine learning.Chinese medicine · 2021Article
- End-to-End Models to Imitate Traditional Chinese Medicine Syndrome Differentiation in Lung Cancer Diagnosis: Model Development and Validation.JMIR medical informatics · 2020Article
- Pulse Wave Cycle Features Analysis of Different Blood Pressure Grades in the Elderly.Evidence-based complementary and alternative medicine : eCAM · 2018Article
- Deep Convolutional Neural Networks for Classifying Body Constitution Based on Face Image.Computational and mathematical methods in medicine · 2017Article
- A research on syndrome element differentiation based on phenomenology and mathematical method.Chinese medicine · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As a complementary and alternative medicine in medical field, traditional Chinese medicine (TCM) has drawn great attention in the domestic field and overseas. In practice, TCM provides a quite distinct methodology to patient diagnosis and treatment compared to western medicine (WM). Syndrome (ZHENG or pattern) is differentiated by a set of symptoms and signs examined from an individual by four main diagnostic methods: inspection, auscultation and olfaction, interrogation, and palpation which reflects the pathological and physiological changes of disease occurrence and development. Patient classification is to divide patients into several classes based on different criteria. In this paper, from the machine learning perspective, a survey on patient classification issue will be summarized on three major aspects of TCM: sign classification, syndrome differentiation, and disease classification. With the consideration of different diagnostic data analyzed by different computational methods, we present the overview for four subfields of TCM diagnosis, respectively. For each subfield, we design a rectangular reference list with applications in the horizontal direction and machine learning algorithms in the longitudinal direction. According to the current development of objective TCM diagnosis for patient classification, a discussion of the research issues around machine learning techniques with applications to TCM diagnosis is given to facilitate the further research for TCM patient classification.
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.