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.

Objective:To determine the carrier frequency and hot-spot variants of a custom-designed expanded carrier screening (ECS) panel with 216 diseases (216-ECS panel) within a Chinese population of childbearing age.Methods:Whole-exome sequencing data from a cohort of 3 097 unrelated healthy individuals (including 1 424 couples) from Peking Union Medical College Hospital between January 2013 and December 2023 were analyzed. Totally 220 genes which inherited in a recessive manner of 216-ECS panel were included in the analysis. The analysis included variant carrier rate, gene carrier rate, cumulative carrier rate, at-risk couple rates, and variant spectrum.Results:(1) Pathogenic variants were identified in 1 472 (47.53%, 1 472/3 097) individuals, with an average of 0.65 pathogenic variants per individual. The rate of at-risk couples was 3.93% (56/1 424). (2) A total of 180 genes were identified, with 16 genes exhibiting a gene carrier rate of ≥1% and 33 genes having a rate of ≥0.5%, most of which were associated with inherited metabolic diseases. Noteworthy genes with higher gene carrier rates and high-frequency variants included GJB2: c.235del, PAH: c.728G>A, ATP7B: c.2333G>T, SLC26A4: c.919-2A>G, GALC: c.1901T>C, POLG: c.2890C>T, SLC22A5: c.1472C>G, USH2A: c.2802T>G, SLC25A13: c.852_855del, GAA: c.761C>T and c.752C>T. Conclusion:This study offers a focused analysis of carrier frequencies and hot-spot variants of 216 diseases of the ECS panel constructed by our laboratory among the Chinese population, laying a foundation for the development of ECS programs tailored to the Chinese population.