Complexity science and traditional Chinese medicine （TCM） share a profound intrinsic compatibility. To address the limitations of reductionist approaches in guiding the dynamically holistic theory and practice of TCM， this paper develops​ a novel research pathway under the guidance of complexity science， using the open complex giant systems （OCGS） theory as its practical framework， upholding the fundamental principles of TCM and breaking new ground of artificial intelligence （AI）. The core tasks of this pathway involve the objectification and structured diagnosis-treatment systems， and the construction of a complex， large-scale TCM model. The paper further delineates the data architecture design and reinforcement learning training pathway. Acknowledging the differences in information processing between the human brain and computers， it proposes a training strategy that minimizes manual labeling of "syndromes" and instead focuses on the training paradigm of "herb-human interaction → syndrome manifestation → dosage adjustment". Under the guidance of complexity science theory， TCM is poised for deep integration with AI technology， driving technological innovation powered by data and computational capabilities.

Lumbar manipulation plays an important role in the non-surgical treatment of lumbar degenerative diseases.Lumbar manipulation is a compound technique that contains many mechanical elements and motion characteristics at the moment of operation.Quantifying and objectifying parameters of the manipulation,summarizing technical characteristics of the operation,and discussing biomechanical mechanism of the manipulation in-depth,can contribute to teaching assessment and clinical diagnosis and treatment standards of the manipulation,making the manipulation safer and efficient,and further promoting inheritance and development of the traditional Chinese medicine manipulation.This article reviews and synthesizes domestic and foreign biomechanical research papers on lumbar manipulation for the treatment of lumbar degenerative diseases in recent years.The biomechanical effects on the lumbar spine and its accessory structures under manual transient loading,the measurement of technical parameters,and the characteristics of manual operation are summarized.

Lumbar manipulation plays an important role in the non-surgical treatment of lumbar degenerative diseases.Lumbar manipulation is a compound technique that contains many mechanical elements and motion characteristics at the moment of operation.Quantifying and objectifying parameters of the manipulation,summarizing technical characteristics of the operation,and discussing biomechanical mechanism of the manipulation in-depth,can contribute to teaching assessment and clinical diagnosis and treatment standards of the manipulation,making the manipulation safer and efficient,and further promoting inheritance and development of the traditional Chinese medicine manipulation.This article reviews and synthesizes domestic and foreign biomechanical research papers on lumbar manipulation for the treatment of lumbar degenerative diseases in recent years.The biomechanical effects on the lumbar spine and its accessory structures under manual transient loading,the measurement of technical parameters,and the characteristics of manual operation are summarized.

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 and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

Background and Objectives: The Fractional Flow Reserve and Intravascular UltrasoundGuided Intervention Strategy for Clinical Outcomes in Patients with Intermediate Stenosis (FLAVOUR) trial demonstrated non-inferiority of fractional flow reserve (FFR)-guided percutaneous coronary intervention (PCI) compared with intravascular ultrasound (IVUS)-guided PCI. We sought to investigate the cost-effectiveness of FFR-guided PCI compared to IVUS-guided PCI in Korea. Methods: A 2-part cost-effectiveness model, composed of a short-term decision tree model and a long-term Markov model, was developed for patients who underwent PCI to treat intermediate stenosis (40% to 70% stenosis by visual estimation on coronary angiography).The lifetime healthcare costs and quality-adjusted life-years (QALYs) were estimated from the healthcare system perspective. Transition probabilities were mainly referred from the FLAVOUR trial, and healthcare costs were mainly obtained through analysis of Korean National Health Insurance claims data. Health utilities were mainly obtained from the Seattle Angina Questionnaire responses of FLAVOUR trial participants mapped to EQ-5D. Results: From the Korean healthcare system perspective, the base-case analysis showed that FFR-guided PCI was 2,451 U.S. dollar lower in lifetime healthcare costs and 0.178 higher in QALYs compared to IVUS-guided PCI. FFR-guided PCI remained more likely to be cost-effective over a wide range of willingness-to-pay thresholds in the probabilistic sensitivity analysis. Conclusions Based on the results from the FLAVOUR trial, FFR-guided PCI is projected to decrease lifetime healthcare costs and increase QALYs compared with IVUS-guided PCI in intermediate coronary lesion, and it is a dominant strategy in Korea.

OBJECTIVE: To evaluate the early effectiveness of navigation-free robot-assisted total knee arthroplasty (TKA) compared to traditional TKA in the treatment of knee osteoarthritis combined with extra-articular deformities. METHODS: The clinical data of 30 patients with knee osteoarthritis combined with extra-articular deformities who met the selection criteria between June 2019 and January 2024 were retrospectively analyzed. Fifteen patients underwent CORI navigation-free robot-assisted TKA and intra-articular osteotomy (robot group) and 15 patients underwent traditional TKA and intra-articular osteotomy (traditional group). There was no significant difference in age, gender, body mass index, affected knee side, extra-articular deformity angle, deformity position, deformity type, and preoperative knee range of motion, American Knee Society (KSS) knee score and KSS function score, and lower limb alignment deviation between the two groups ( P>0.05). The operation time, intraoperative blood loss, and complications of the two groups were recorded and compared. The knee range of motion and lower limb alignment deviation were recorded before operation and at 6 months after operation, and the knee joint function was evaluated by KSS knee score and function score. RESULTS: There was no significant difference in operation time between the two groups ( P>0.05); the intraoperative blood loss in the robot group was significantly less than that in the traditional group ( P<0.05). Patients in both groups were followed up 6-12 months, with an average of 8.7 months. The incisions of all patients healed well, and there was no postoperative complication such as thrombosis or infection. At 6 months after operation, X-ray examination showed that the position of the prosthesis was good in both groups, and there was no loosening or dislocation of the prosthesis. The knee joint range of motion, the lower limb alignment deviation, and the KSS knee score and KSS function score significantly improved in both groups ( P<0.05) compared to preoperative ones. The changes of lower limb alignment deviation and KSS function score between pre- and post-operation in the robot group were significantly better than those in the traditional group ( P<0.05), while the changes of other indicators between pre- and post-operation in the two groups were not significant ( P>0.05). CONCLUSION Compared to traditional TKA, navigation-free robot-assisted TKA for knee osteoarthritis with extra-articular deformities results in less intraoperative blood loss, more precise reconstruction of lower limb alignment, and better early effectiveness. However, long-term effectiveness require further investigation.
Humans ; Arthroplasty, Replacement, Knee/methods* ; Osteoarthritis, Knee/surgery* ; Robotic Surgical Procedures/methods* ; Male ; Female ; Retrospective Studies ; Range of Motion, Articular ; Middle Aged ; Aged ; Treatment Outcome ; Osteotomy/methods* ; Knee Joint/physiopathology* ; Operative Time

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.