Current Status and Research Progress of Artificial Intelligence in the Application of Lumbar Degenerative Diseases
LI Chao
LI Wenchao
GUO Hong
TANG Zhenyu
YU Pengfei
ZHU Guangye
MA Zhijia
LI Hongwei
Abstract：Lumbar degenerative diseases are more common in middle-aged and elderly people,mainly manifested as lower back and lower limb pain,functional impairment,and decreased quality of life.With the increasing aging of the population,more and more degenerative diseases of the lumbar spine are troubling people,seriously affecting their quality of life.The types of degenerative diseases of the lumbar spine are complex and diverse,and the diagnosis and treatment are difficult.For a long time,accurate diagnosis and treatment have been the focus of scholars'research.In recent years,the concept of combining medicine and engineering has gradually gained attention in improving the diagnostic accuracy and surgical success rate of lumbar degenerative diseases.With the rapid development of artificial intelligence(AI),its efficient computing power can simulate the occurrence,development,and prognosis of diseases,which is of great significance for the diagnosis,treatment,and evaluation of diseases.At present,combining AI technology with the diagnosis and treatment of spinal surgery diseases has become a research hotspot in the field of spinal surgery.The introduction of AI can help reduce the difficulty of diagnosis and treatment of lumbar degenerative diseases.This article discusses the application of AI technology in the diagnosis and treatment of lumbar degenerative diseases in recent years,including the principles and clinical practices of medical image analysis,assisted diagnosis,intraoperative application,and postoperative complication prediction,in order to provide new ideas for promoting the efficient combination of AI and lumbar degenerative disease diagnosis and treatment.
Keywords：artificial intelligencelumbar degenerative diseasesdeep learningrobotic surgery
Publication Date：2026-03-20
Online Publishing Date：2026-07-17(First online date of this platform, not the publication date of the document)
Pages：6( 85-90 )