Innovative Development Measures of the Chinese Medicine Industry in Industrial Big Data with the Aid of AI in the Context of an Imperfectly Competitive Market Economy

• Published in: Applied artificial intelligence Vol. 37; no. 1
• Main Author: Wang, Li
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 31.12.2023; Taylor & Francis Ltd; Taylor & Francis Group
• Subjects: Algorithms; Artificial intelligence; Big Data; Industrial development; Market economies; Materials selection; Raw materials; Recurrent neural networks; Traditional Chinese medicine
• ISSN: 0883-9514; 1087-6545
• DOI: 10.1080/08839514.2023.2215095

The use of traditional Chinese medicine for healthcare has been on the rise in recent years, leading to the rapid development of the industry in China. However, the industry still faces several challenges, including the supply of raw materials, changing market demands, and competition from foreign competitors, especially during the current era of rampant epidemics. To address these challenges, advanced technologies such as artificial intelligence (AI) can play a significant role in enhancing the innovation and competitiveness of the Chinese medicine industry. One such technology is the Long Short-Term Memory (LSTM) algorithm, a recurrent neural network that has proven effective in processing and analyzing sequential data. By utilizing this algorithm, the Chinese medicine industry can harness the vast amounts of data generated during various stages of production, from raw material selection to clinical practice. This can optimize processes, improve product quality, and enhance treatment outcomes.