BACKGROUND:In recent years,artificial intelligence has been increasingly integrated into the diagnosis and treatment of lumbar disc herniation,enhancing the accuracy and efficiency of diagnostic procedures and diversifying therapeutic approaches.This integration has positioned artificial intelligence as a burgeoning focal point within the field.OBJECTIVE:To provide a comprehensive overview of the current applications of artificial intelligence in the diagnosis and treatment of lumbar disc herniation,to analyze the limitations of the relevant technologies.METHODS:A systematic computer-assisted literature search was performed in PubMed,CNKI,WanFang Database,and VIP Database for relevant publications regarding the application of artificial intelligence in the diagnosis and treatment of lumbar disc herniation from database inception up to August 2024.The search keywords included"lumbar disc herniation,artificial intelligence,machine learning,deep learning,big data,robot,neural network,model,algorithm."A total of 101 articles were selected based on predefined inclusion criteria and were reviewed.RESULTS AND CONCLUSION:Different artificial intelligence technologies have propelled the intelligent treatment of lumbar disc herniation,showing great potential for future development.Deep learning technology,based on advanced algorithms,constructs corresponding learning models to optimize the processing of X-ray,CT,and MRI images,achieving precise localization,identification,and analysis of degenerated intervertebral discs,and improving the accuracy of automated diagnosis.Big data technology utilizes data platforms to analyze vast medical data,simulate disease development trends,and provide a new perspective for disease assessment and prediction.Surgical robots,combined with robotic arms,3D high-definition vision systems,and 5G communication technology,support remote precise surgical operations,demonstrating significant technological advantages.In the future,the diagnosis and treatment of lumbar disc herniation by artificial intelligence will evolve towards standardization,efficiency,and precision through continuous optimization of algorithms and the professional development of data platforms.

BACKGROUND:In recent years,artificial intelligence has been increasingly integrated into the diagnosis and treatment of lumbar disc herniation,enhancing the accuracy and efficiency of diagnostic procedures and diversifying therapeutic approaches.This integration has positioned artificial intelligence as a burgeoning focal point within the field.OBJECTIVE:To provide a comprehensive overview of the current applications of artificial intelligence in the diagnosis and treatment of lumbar disc herniation,to analyze the limitations of the relevant technologies.METHODS:A systematic computer-assisted literature search was performed in PubMed,CNKI,WanFang Database,and VIP Database for relevant publications regarding the application of artificial intelligence in the diagnosis and treatment of lumbar disc herniation from database inception up to August 2024.The search keywords included"lumbar disc herniation,artificial intelligence,machine learning,deep learning,big data,robot,neural network,model,algorithm."A total of 101 articles were selected based on predefined inclusion criteria and were reviewed.RESULTS AND CONCLUSION:Different artificial intelligence technologies have propelled the intelligent treatment of lumbar disc herniation,showing great potential for future development.Deep learning technology,based on advanced algorithms,constructs corresponding learning models to optimize the processing of X-ray,CT,and MRI images,achieving precise localization,identification,and analysis of degenerated intervertebral discs,and improving the accuracy of automated diagnosis.Big data technology utilizes data platforms to analyze vast medical data,simulate disease development trends,and provide a new perspective for disease assessment and prediction.Surgical robots,combined with robotic arms,3D high-definition vision systems,and 5G communication technology,support remote precise surgical operations,demonstrating significant technological advantages.In the future,the diagnosis and treatment of lumbar disc herniation by artificial intelligence will evolve towards standardization,efficiency,and precision through continuous optimization of algorithms and the professional development of data platforms.

Recent studies heve demonstrated that Akkermansia muciniphila (A.muciniphila) plays an important role in human health and disease , including regulating the development of the immune system and the metabolic phenotype of the host.This article reviews the research progress on A.muciniphila in recent years, focusing on the basic characteristics , the influencing factors of colonization , and the underlying mechanism of maintaining intestinal homeostasis of A.muciniphila.Additionally, the article summarizes the potential association between A.muciniphila and the chronic metabolic diseases such as obesity , atherosclerosis,diabetes mellitus and infectious diseases.The perspect of A.muciniphila as a new generation of probiotics in clinical medicine and the challenge for its industrialization are also discussed in the article .

Objective To investigate the disease types incurring poverty, patient population layout, and cost burden by poor households due to illness. Methods During the time August 17-24,2017, App questionnaires were used onsite for data survey at 2 824 poor hourseholds in Nanyang city of Henan province, in order to learn the impacts of the poverty-causing diseases on the labor capacity of the patients and the cost burdens. Such methods as descriptive analysis, rank sum test and correlation analysis were used for data analysis. Results The survey found that 61.79 percent(1 745 households) of the poor households turned poor by illness, most of them aged 40 to 60 years old. The ten disease categories, namely cerebrovascular diseases, malignant tumor, ischemic heart diseases and mental diseases, constitute top disease causes of poverty. These diseases significantly damage their labor capacity, up to 37.67% of them totally disabled. The self-paid expenses of the patients per year accounted for 57.22% of the total annual expenses. Conclusions Medical insurance policies need to elevate the scope and efforts of medical compensation;public health services need to improve health promotion and health education; government supervision needs to be enhanced to keep minimizing patients′disease burdens.