Application of Artificial Intelligence to Toxicological Assessment of Plant: A Bibliometric Analysis and Future Research Plans
Artificial intelligence (AI) has been gaining attention in health science with extensive application in the toxicological assessment of plants in several studies published on this topic. However, there is a dire need for bibliometric analysis of publications to chart research topic direction proposed advances for future research. A bibliometric analysis explores core articles on the toxicological assessment of plants and identifies any unsolved issues regarding the use of AI in the discovery of toxicity of plants used in pharmacological research. Articles published from January 2008 to December 2023 were retrieved from Scopus for bibliometric analysis. The study finds that there was an annual increase in the number of published articles with a drastic increase between 2019 and 2023. Ultimately, the study included 77 research articles in the bibliometric analysis. The articles that are related to the application of AI in drug toxicity assessment are categorized into four main clusters: AI application cluster, drug development, toxicity prediction model, and assessment of the outcome from drug adverse events. “artificial intelligence” has the highest frequency keyword, followed by “drug toxicity”, human, machine learning, and drug discovery. The United States of America (USA) had the highest, followed by China and India in the order of 29, 11, and 8 respectively while the United Kingdom had only 4 articles. This study suggests dire trend towards toxicity prediction in drug discovery and development. However, few of the trials have suggested precise conclusions about the potential of AI in toxicity prediction for drug discovery and development.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.