Using AI deep learning to verify the effect of herbal ingredients in blue-green algae nano-grade liver-nourishing tea on liver repair and treatment

Main Article Content

Chien Hua Liao Wei-Yuan Ho Hsing-Chung Chen

Abstract

This study aims to explore the mechanism of action of the herbal ingredients in the blue-green algae nano liver-nourishing tea compound on liver repair and therapeutic potential, and to combine AI deep learning technology for systematic efficacy verification and prediction. Liver diseases (such as fatty liver, chronic hepatitis, and liver fibrosis) have gradually become younger in recent years, posing a major threat to public health; Chinese herbal medicine has long-term clinical application experience in the field of liver health, but its scientific mechanism and dosage form optimization lack integrated evidence. This study selected adjuvants containing blue-green algae (such as Spirulina, Aphanizomenon flos-aquae) and traditional liver-nourishing herbal medicines (such as Artemisia capillaris, Citrus aurantium, Schisandra chinensis, Bupleurum, and Scutellaria baicalensis), combined with nanocarrier technology to enhance the bioavailability and hepatocyte penetration of its active ingredients, and used AI models to analyze its key pathways of antioxidant, anti-inflammatory, and hepatocyte regeneration. The efficacy of soaking time was also studied; short-term hot soaking in hot water (such as 100°C, 5-15 minutes) can efficiently extract polyphenols and antioxidants, and has the best effect on improving ALT/AST. By collecting and integrating more than 300 articles and database data such as TCMSP and PubChem in the past five years, Transformer-based deep semantic models and pharmacological network analysis were used to perform association comparisons and action pathway predictions. The analysis results showed that the compound can simultaneously activate the Nrf2-ARE antioxidant pathway, inhibit NF-κB inflammatory signals, and promote liver cell repair and regeneration through PI3K/Akt and MAPK pathways. In addition, the chlorophyll, phycocyanin and small molecule peptides rich in blue-green algae have liver toxicity elimination and immune regulation functions, and show synergistic effects with Chinese herbal medicine ingredients. The author personally drew a map of the phagocytic effect of the immune mechanism of hepatocytes; and used AI prediction results to verify the accuracy of the ROC curve with an AUC of 0.91, and used radar charts and forest charts to present the main efficacy distribution and mechanism weights, showing that this compound has the potential to become a non-toxic, highly compatible liver adjuvant treatment program. In the future, it is planned to further introduce animal pre-clinical trials and conduct more human trials (IRB) to verify its efficacy and safety, and provide an innovative application basis for liver health and functional plant tea products. It is an internationally effective and valuable health and liver protection drink; it is worthy of mass production by food and pharmaceutical factories to benefit the world and benefit the people.

Keywords: AI deep learning, blue-green algae, nano-grade liver-nourishing tea, Chinese herbal ingredients, liver repair treatment, outcome mechanism

Article Details

How to Cite
LIAO, Chien Hua; HO, Wei-Yuan; CHEN, Hsing-Chung. Using AI deep learning to verify the effect of herbal ingredients in blue-green algae nano-grade liver-nourishing tea on liver repair and treatment. Medical Research Archives, [S.l.], v. 13, n. 8, aug. 2025. ISSN 2375-1924. Available at: <https://esmed.org/MRA/mra/article/view/6809>. Date accessed: 05 dec. 2025. doi: https://doi.org/10.18103/mra.v13i8.6809.
Section
Research Articles

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