Objective: To systematically evaluate the performance of machine learning (ML) models in predicting non suicidal self injury (NSSI) behavior among adolescents, providing an evidence based foundation for the development of clinically applicable risk assessment tools. Methods: A comprehensive search was conducted in PubMed, Embase, Web of Science, CNKI, and Wanfang databases for relevant studies from their inception to July 21, 2025. The Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to evaluate the methodological quality of the included studies. Stata 18 software was used to calculate the area under the receiver operating characteristic curve (AUC) of the models, and publication bias assessment, sensitivity analysis, and Egger s test were performed. Results: The total of 12 studies (42 prediction models) involving 58 070 adolescents were included. There were 15 machine learning algorithms in total, among which Random Forest, Logistic Regression, XGBoost, and Support Vector Machines were the most frequently utilized. The most common predictors were gender (female), family function, depression, emotion regulation, and age. All 12 included studies exhibited a high risk of bias. The pooled AUC was 0.80 (95% CI =0.78-0.82), although heterogeneity was substantial ( I 2=95.8%, P <0.01). Sensitivity analysis confirmed the robustness of these findings (no overlap in 95% CI ), while Egger s test indicated the presence of publication bias ( P <0.05). Conclusions Machine learning demonstrates potential in the risk prediction of adolescent NSSI, but existing models have a high risk of bias. Future research should focus on improving methodological quality and optimizing model reliability through rigorous external validation.

Liver Cancer is a prevalent malignant tumor worldwide,with various treatment options available. Among these, ablation therapy holds a significant role in liver cancer treatment due to its minimally invasive nature and lower complication rate. This article reviews the indications and contraindications of liver cancer ablation,the basic principles of different ablation techniques,and their advantages and limitations in clinical applications for liver cancer. Each ablation technique possesses unique characteristics regarding therapeutic efficacy,application scope,and complication profiles,necessitating the selection of the most appropriate approach tailored to the patient′s specific condition and tumor attributes. Furthermore,this article also discusses the potential role of ablation therapy in multidisciplinary treatment,highlighting its synergistic application with liver transplantation,interventional therapy,and immunotargeted therapy to significantly improve outcomes for unresectable liver cancer. Specifically,ablation therapy can induce an anti-tumor immune response by locally destroying the tumor,offering a potential application prospect for combining ablation with immunotherapy. Looking forward,with advances in nanotechnology,artificial intelligence,and image-guided techniques,ablation therapy is expected to progress towards higher precision,personalization,and safety,offering optimized treatment options for liver cancer patients.

Liver Cancer is a prevalent malignant tumor worldwide,with various treatment options available. Among these, ablation therapy holds a significant role in liver cancer treatment due to its minimally invasive nature and lower complication rate. This article reviews the indications and contraindications of liver cancer ablation,the basic principles of different ablation techniques,and their advantages and limitations in clinical applications for liver cancer. Each ablation technique possesses unique characteristics regarding therapeutic efficacy,application scope,and complication profiles,necessitating the selection of the most appropriate approach tailored to the patient′s specific condition and tumor attributes. Furthermore,this article also discusses the potential role of ablation therapy in multidisciplinary treatment,highlighting its synergistic application with liver transplantation,interventional therapy,and immunotargeted therapy to significantly improve outcomes for unresectable liver cancer. Specifically,ablation therapy can induce an anti-tumor immune response by locally destroying the tumor,offering a potential application prospect for combining ablation with immunotherapy. Looking forward,with advances in nanotechnology,artificial intelligence,and image-guided techniques,ablation therapy is expected to progress towards higher precision,personalization,and safety,offering optimized treatment options for liver cancer patients.

To better analyze the problem of abnormal neuromuscular coupling related to motor dysfunction for stroke patients, the functional coupling of the multichannel electromyography (EMG) were studied and the difference between stroke patients and healthy subjects were further analyzed to explore the pathological mechanism of motor dysfunction after stroke. Firstly, the cross-frequency coherence (CFC) analysis and non-negative matrix factorization (NMF) were combined to construct a CFC-NMF model to study the linear coupling relationship in bands and the nonlinear coupling characteristics in different frequency ratios during elbow flexion and extension movement. Furthermore, the significant coherent area and sum of cross-frequency coherence were respectively calculated to quantitatively describe the intermuscular linear and nonlinear coupling characteristics. The results showed that the linear coupling relationship between multichannel muscles was different in frequency bands and the overall coupling was stronger in low frequency band. The linear coupling strength of the stroke patients was lower than that of the healthy subjects in different frequency bands especially in beta and gamma bands. For the nonlinear coupling, the intermuscular coupling strength of stroke patients in different frequency ratios was significantly lower than that of the healthy subjects, and the coupling strength in the frequency ratio 1∶2 was higher than that in the frequency ratio 1∶3. This method can provide a theoretical basis for exploring the intermuscular coupling mechanism of patients with motor dysfunction.
Case-Control Studies ; Electromyography ; Humans ; Muscle, Skeletal ; physiopathology ; Stroke ; physiopathology ; Stroke Rehabilitation