Hepatology international · 2025
Trends in the applications of artificial intelligence in fatty liver diseases.
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Xie Tian-Ao, Liufu Li-Li, Chen Hui-Jin, Chen Hao-Lin, Hou Xin-Ting, Wang Xuan-Rui, Han Meng-Yi, Shan Yu-Kai, Shen Rui-Jing, Wu Zhong-Yu, Li Shi-Jie, Juengpanich Sarun, Topatana Win
Аннотация
INTRODUCTION: Artificial intelligence (AI) has rapidly advanced and shows great potential in the prediction, diagnosis, treatment, and prognosis of fatty liver disease (FLD). This study aims to summarize AI's applications and emerging trends in FLD to inspire future research directions.
METHOD: We analyzed 270 articles sourced from the Web of Science Core Collection published between 2006 and 2024. The study focuses on the medical application of AI in FLD, examining the contributions of authors, institutions, countries, keywords, and cited references.
RESULTS: AI is predominantly applied in FLD diagnosis, with progression from simple diagnostic tools to advanced methods for classifying FLD and assessing liver fat content. Moreover, the types of data used in AI development have evolved, incorporating a variety of new image and clinical data sources. AI is also being integrated into drug development and personalized nutritional therapies for FLD. Additionally, researchers are becoming increasingly interested in the application of AI to study FLD genes.
CONCLUSION: We found that the applications of AI in FLD are mainly reflected in the prediction, diagnosis, therapy, and prognosis of FLD. In contrast to traditional medicine, AI has the potential to advance the fields of precision medicine and telemedicine, as well as to conserve additional social resources. Moreover, AI may help medical personnel from the perspective of traditional Chinese medicine, FLD prognosis, and the use of AI to analyze gene prediction and natural language processing (NLP).
METHOD: We analyzed 270 articles sourced from the Web of Science Core Collection published between 2006 and 2024. The study focuses on the medical application of AI in FLD, examining the contributions of authors, institutions, countries, keywords, and cited references.
RESULTS: AI is predominantly applied in FLD diagnosis, with progression from simple diagnostic tools to advanced methods for classifying FLD and assessing liver fat content. Moreover, the types of data used in AI development have evolved, incorporating a variety of new image and clinical data sources. AI is also being integrated into drug development and personalized nutritional therapies for FLD. Additionally, researchers are becoming increasingly interested in the application of AI to study FLD genes.
CONCLUSION: We found that the applications of AI in FLD are mainly reflected in the prediction, diagnosis, therapy, and prognosis of FLD. In contrast to traditional medicine, AI has the potential to advance the fields of precision medicine and telemedicine, as well as to conserve additional social resources. Moreover, AI may help medical personnel from the perspective of traditional Chinese medicine, FLD prognosis, and the use of AI to analyze gene prediction and natural language processing (NLP).