What type of study is this?

This is a Quantitative Study study (also classified as: Experimental Study).

September 26, 2025Theoretical and Natural ScienceOpen Access

Herbal Medicine in the Molecular Era: Integrating Traditional Chinese Herb Signatures with Chemotherapy Efficacy and Tumor Microenvironment Using Machine Learning Models

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Authors

XZXin-Lan Zhang

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Implication

Research reveals machine learning enhances chemosensitivity predictions in metastatic melanoma using traditional chinese medicine signatures, suggesting improved cancer therapies.

Key Points

High herb regulatory scores correlate with improved overall survival and increased immune infiltration in melanoma.
Nonlinear machine learning models achieved robust discrimination in predicting chemosensitivity for cancer treatments.
Extracts from WuHuaGuo and JiuCengTa inhibited melanoma cell growth and activated T-cell markers in vitro.
A unified framework combining computational and experimental approaches can lead to novel adjuvant therapies in cancer.

Cite This Study

Xin-Lan Zhang (2025) studied this question.

synapsesocial.com/papers/68d6c68eb1249cec298b2e08 https://doi.org/10.54254/2753-8818/2025.au27079

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Implication

Research reveals machine learning enhances chemosensitivity predictions in metastatic melanoma using traditional chinese medicine signatures, suggesting improved cancer therapies.

Herbal Medicine in the Molecular Era: Integrating Traditional Chinese Herb Signatures with Chemotherapy Efficacy and Tumor Microenvironment Using Machine Learning Models

Discussion

Member takes

Implication

Key Points

Cite This Study

Herbal Medicine in the Molecular Era: Integrating Traditional Chinese Herb Signatures with Chemotherapy Efficacy and Tumor Microenvironment Using Machine Learning Models

Discussion

Member takes

Implication

Key Points

Cite This Study

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