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Medicine, Chinese Traditional

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An Ontology-Based Artificial Intelligence Model for Medicine Side-Effect Prediction: Taking Traditional Chinese Medicine as an Example.

Computational and mathematical methods in medicine
In this work, an ontology-based model for AI-assisted medicine side-effect (SE) prediction is developed, where three main components, including the drug model, the treatment model, and the AI-assisted prediction model, of the proposed model are prese...

System-Pharmacology Dissection of Traditional Chinese herbs SINI Decoction for Treatment of Cardiovascular Diseases.

Anais da Academia Brasileira de Ciencias
Abstract: Cardiovascular diseases (CVDs) are leading causes of death in the world, owing to noticeable incidence and mortality. Traditional Chinese Medicine (TCM) SINI Decoction (SND) is used to prevent and treat CVDs, which has attracted extensive ...

Artificial Intelligence Approach To Investigate the Longevity Drug.

The journal of physical chemistry letters
Longevity is a very important and interesting topic, and has been demonstrated to be related to longevity. We combined network pharmacology, machine learning, deep learning, and molecular dynamics (MD) simulation to investigate potent lead drugs. Re...

Evaluation and Identification of the Neuroprotective Compounds of Xiaoxuming Decoction by Machine Learning: A Novel Mode to Explore the Combination Rules in Traditional Chinese Medicine Prescription.

BioMed research international
Xiaoxuming decoction (XXMD), a classic traditional Chinese medicine (TCM) prescription, has been used as a therapeutic in the treatment of stroke in clinical practice for over 1200 years. However, the pharmacological mechanisms of XXMD have not yet b...

An ontological framework for the formalization, organization and usage of TCM-Knowledge.

BMC medical informatics and decision making
BACKGROUND: The traditional Chinese Medicine Language System (TCMLS) is a large-scale terminology system, developed from 2002 on by the Institute of Information of Traditional Chinese Medicine (IITCM). Until now, more than 120,000 concepts, 300,000 t...

Deep Learning and Random Forest Approach for Finding the Optimal Traditional Chinese Medicine Formula for Treatment of Alzheimer's Disease.

Journal of chemical information and modeling
It has demonstrated that glycogen synthase kinase 3β (GSK3β) is related to Alzheimer's disease (AD). On the basis of the world largest traditional Chinese medicine (TCM) database, a network-pharmacology-based approach was utilized to investigate TCM ...

Complexity perception classification method for tongue constitution recognition.

Artificial intelligence in medicine
The body constitution is much related to the diseases and the corresponding treatment programs in Traditional Chinese Medicine. It can be recognized by the tongue image diagnosis, so that it is essentially regarded as a problem of tongue image classi...

Simultaneous quantification of six indicator compounds in Wen-Qing-Yin by high-performance liquid chromatography-diode array detection.

Journal of food and drug analysis
A simple gradient high-performance liquid chromatography with diode array detection (HPLC-DAD) method was used to simultaneously to analyze characteristics of six indicator compounds in the traditional Chinese medicine (TCM) formulation Wen-Qing-Yin ...

Neural network analysis of Chinese herbal medicine prescriptions for patients with colorectal cancer.

Complementary therapies in medicine
Traditional Chinese Medicine (TCM) is an experiential form of medicine with a history dating back thousands of years. The present study aimed to utilize neural network analysis to examine specific prescriptions for colorectal cancer (CRC) in clinical...

Application of Chemometric Algorithms in the High-Performance Thin-Layer Chromatography Fingerprint of Traditional Chinese Medicines.

Journal of AOAC International
The use of HPTLC fingerprinting for the analysis of traditional Chinese medicines (TCMs) usually involves several image-processing steps. However, these image-processing steps are time consuming. We describe a new approach that applies artificial n...