Recognition and quality mapping of traditional herbal drugs:way forward towards artificial intelligence  

作　　者：Sanyam Sharma Subh Naman Ashish Baldi 

机构地区：[1]Faculty of Pharmacy,Pacific Academy of Higher Education and Research University,Udaipur 313024,India [2]Pharma Innovation Lab,Department of Pharmaceutical Sciences and Technology,Maharaja Ranjit Singh Punjab Technical University,Bathinda 151001,India [3]Faculty of Pharmaceutical Sciences,The ICFAI University,Baddi 174103,India.

出　　处：《Traditional Medicine Research》2025年第1期12-26,共15页TMR传统医学研究

摘　　要：The use of traditional herbal drugs derived from natural sources is on the rise due to their minimal side effects and numerous health benefits.However,a major limitation is the lack of standardized knowledge for identifying and mapping the quality of these herbal medicines.This article aims to provide practical insights into the application of artificial intelligence for quality-based commercialization of raw herbal drugs.It focuses on feature extraction methods,image processing techniques,and the preparation of herbal images for compatibility with machine learning models.The article discusses commonly used image processing tools such as normalization,slicing,cropping,and augmentation to prepare images for artificial intelligence-based models.It also provides an overview of global herbal image databases and the models employed for herbal plant/drug identification.Readers will gain a comprehensive understanding of the potential application of various machine learning models,including artificial neural networks and convolutional neural networks.The article delves into suitable validation parameters like true positive rates,accuracy,precision,and more for the development of artificial intelligence-based identification and authentication techniques for herbal drugs.This article offers valuable insights and a conclusive platform for the further exploration of artificial intelligence in the field of herbal drugs,paving the way for smarter identification and authentication methods.

关 键 词：artificial intelligence AYURVEDA machine learning models herbal drugs image pre-processing medicinal plants 

分 类 号：R281[医药卫生—中药学] TP18[医药卫生—中医学]