Artificial Intelligence perspectives in advancing Persian Herbal Medicine: A systematic review

IF 1.7 Q2 Medicine

Advances in integrative medicine Pub Date : 2025-03-05 DOI:10.1016/j.aimed.2025.03.001

Somaieh Soltani , Laleh khodaie , Vilas Surana

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引用次数: 0

Abstract

Background and aim

In Persian Medicine (PM), herbal remedies are crucial in preventing and treating disease. The potential of AI has yet to be investigated in Persian Herbal Medicine (PHM). This study aimed to explore the potential of AI in PHM.

Methods

Five databases were used to collect data for this systematic review. Considering inclusion and exclusion criteria and quality assessment of the included papers led to a search strategy flowchart.

Results and discussion

AI, ML, and DL facilitated data analysis by prediction and pattern recognition. Predictive modeling could prognosticate herbal ingredients and chromatographic conditions, mechanism of action, toxicity, side effects, drug candidates and drug-target interactions, pharmaco-therapeutic effects, suitable drug delivery system, and interaction between drugs and herbs used in PM. Pattern recognition assists in recognizing associations among the identification of plant species, chemical ecology, optimum cultivation, harvesting conditions, and regeneration of threatened species. The mentioned facilities bring about drug discovery, standardization, and data Integration to acquire better patient outcomes, treatment, and personalized medicine. Natural medicine databases could be used to extract data for PHM. The challenges of using AI in PHM should be addressed. Since AI systems in healthcare rely on large amounts of patient data, ethical issues could be raised, and the protection of personal information necessitated. Incomplete, inaccurate data or biased algorithms and discrimination may occur.

Conclusion

The relationship between traditional herbal practices and cutting-edge technologies provides a more comprehensive and integrated healthcare approach, marking a transformative step towards optimized patient care and natural drug discovery.

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人工智能在推进波斯草药医学中的应用：系统综述

背景和目的在波斯医学（PM）中，草药在预防和治疗疾病方面至关重要。人工智能在波斯草药（PHM）中的潜力尚未得到研究。本研究旨在探索人工智能在PHM中的潜力。方法本系统评价采用5个数据库进行资料收集。考虑纳入和排除标准以及对纳入论文的质量评估，得出了检索策略流程图。ai、ML和DL通过预测和模式识别促进了数据分析。预测模型可以预测中药成分和色谱条件、作用机制、毒性、副作用、候选药物和药物-靶点相互作用、药物-治疗效果、合适的给药系统以及PM中使用的药物与中药之间的相互作用。模式识别有助于识别植物物种识别、化学生态学、最佳栽培、收获条件和濒危物种再生之间的联系。上述设施带来了药物发现、标准化和数据集成，以获得更好的患者结果、治疗和个性化医疗。天然药物数据库可用于PHM的数据提取。在PHM中使用AI的挑战应该得到解决。由于医疗领域的人工智能系统依赖于大量的患者数据，因此可能会引发伦理问题，并且有必要保护个人信息。可能会出现不完整、不准确的数据或有偏见的算法和歧视。结论传统草药与尖端技术的结合提供了一种更全面、更综合的医疗保健方法，标志着向优化患者护理和天然药物发现迈出了革命性的一步。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in integrative medicine INTEGRATIVE & COMPLEMENTARY MEDICINE-

CiteScore

3.20

自引率

11.80%

发文量

审稿时长

15 weeks

期刊介绍： Advances in Integrative Medicine (AIMED) is an international peer-reviewed, evidence-based research and review journal that is multi-disciplinary within the fields of Integrative and Complementary Medicine. The journal focuses on rigorous quantitative and qualitative research including systematic reviews, clinical trials and surveys, whilst also welcoming medical hypotheses and clinically-relevant articles and case studies disclosing practical learning tools for the consulting practitioner. By promoting research and practice excellence in the field, and cross collaboration between relevant practitioner groups and associations, the journal aims to advance the practice of IM, identify areas for future research, and improve patient health outcomes. International networking is encouraged through clinical innovation, the establishment of best practice and by providing opportunities for cooperation between organisations and communities.