Due to the small scale, low technical level, and limited scope of application of artificial intelligence in the field of traditional Chinese medicine orthopedics, there are many problems in the development of this area. Driven by precise and minimally invasive medical concepts, the integration of artificial intelligence and data mining technologies (such as the Internet, cloud computing, and big data) will further profoundly change the face of smart healthcare in the future, which will bring great challenges to traditional Chinese medicine orthopedics, and Change opportunities for your own development. In order for artificial intelligence to provide good diagnosis and treatment services for a large number of patients with orthopaedic diseases, progress still needs to be made with the technology and joint efforts of many orthopaedic experts and scholars. This article uses data mining techniques to optimize orthopedic rehabilitation information. Test results show that the system is faster and more convenient. Artificial intelligence technology will be used for intelligent medical treatment of orthopedic diseases in the future. It will become an essential assistant for clinicians and make a significant contribution to the diagnosis of various orthopedic diseases.

Biodegradable iron alloy implants have become one of the most ideal possible candidates because of their biocompatibility and comprehensive mechanical properties. Iron alloy’s impact on chondrocytes is still unknown, though. This investigation looked at the biocompatibility and degradation of the Fe30Mn0.6N alloy as well as how it affected bone formation and chondrocyte autophagy. In vivo implantation of Fe30Mn0.6N and Ti6Al4V rods into rabbit femoral cartilage and femoral shaft was carried out to evaluate the degradation of the alloy and the cartilage and bone response at different intervals. After 8 weeks of implantation, the cross‐sectional area of the Fe30Mn0.6N alloys lowered by 50.79 ± 9.59%. More Ca and P element deposition was found on the surface Fe30Mn0.6N rods by using energy dispersive spectroscopy (EDS) and scanning electron microscopy (P < 0.05). After 2, 4, and 8 weeks of implantation, no evident inflammatory infiltration was seen in peri‐implant cartilage and bone tissue of Fe30Mn0.6N and Ti6Al4V alloys. Also, implantation of Fe30Mn0.6N alloy promoted autophagy in cartilage by detecting expression of LC3‐II compared with Ti6Al4V after implantation (P < 0.05). Fe30Mn0.6N alloy also stimulated early osteogenesis at the peri‐implant interface compared with Ti6Al4V after implantation (P < 0.05). In the in vitro test, we found that low concentrations of Fe30Mn0.6N extracts had no influence on cell viability. 15% and 30% extracts of Fe30Mn0.6N could upregulate autophagy compared to the control group by detecting beclin‐1, LC3, Atg3, and P62 on the basis of WB and IHC (P < 0.05). Also, the PI3K‐AKT‐mTOR signaling pathway mediated in the upregulation of autophagy of chondrocytes resulting in exposure to extract of Fe30Mn0.6N alloy. It is concluded that Fe30Mn0.6N showed degradability and biocompatibility in vivo and upregulated autophagy activity in chondrocytes.

Objective To examine the mediating role of positive psychological resources in the relationship between social support and sleep quality among kidney transplant recipients, and to provide evidence for the development of targeted sleep quality interventions. Methods A convenience sample of 343 stable kidney transplant recipients, including both inpatients and outpatients, was recruited from a tertiary hospital in Shenyang, Liaoning Province, China, between December 2024 and June 2025. Data were collected using a general information questionnaire, the Pittsburgh Sleep Quality Index (PSQI), the Social Support Rating Scale(SSRS), the Connor-Davidson Resilience Scale(CD-RISC), and the General Self-Efficacy Scale(GSES). Statistical analyses and path modeling were performed with SPSS 29.0 and AMOS 24.0. Results The prevalence of sleep disorders among kidney transplant recipients was 34.7%. Correlation analyses revealed that PSQI scores were negatively associated with social support, self-efficacy, and resilience (p < 0.01). Social support was positively correlated with self-efficacy and resilience (p < 0.01), and self-efficacy was positively correlated with resilience (p < 0.01). Path analysis showed that self-efficacy and resilience partially mediated the association between social support and sleep quality. The mediating effect of self-efficacy accounted for 51.5% of the total effect, while the mediating effect of resilience accounted for 52.4%. Conclusion Positive psychological resources, particularly self-efficacy and resilience, play a partial mediating role in the relationship between social support and sleep quality in kidney transplant recipients. These findings underscore the importance of incorporating psychological resource enhancement into clinical interventions to improve sleep outcomes in this population.