BACKGROUND:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

OBJECTIVE: To evaluate the effect of biodegradable magnesium alloy materials in promoting tendon-bone healing during rotator cuff tear repair and to investigate their potential underlying biological mechanisms. METHODS: Forty-eight 8-week-old Sprague Dawley rats were taken and randomly divided into groups A, B, and C. Rotator cuff tear models were created and repaired using magnesium alloy sutures in group A and Vicryl Plus 4-0 absorbable sutures in group B, while only subcutaneous incisions and sutures were performed in group C. Organ samples of groups A and B were taken for HE staining at 1 and 2 weeks after operation to evaluate the safety of magnesium alloy, and specimens from the supraspinatus tendon and proximal humerus were harvested at 2, 4, 8, and 12 weeks after operation. The specimens were observed macroscopically at 4 and 12 weeks after operation. Biomechanical tests were performed at 4, 8, and 12 weeks to test the ultimate load and stiffness of the healing sites in groups A and B. At 2, 4, and 12 weeks, the specimens were subjected to the following tests: Micro-CT to evaluate the formation of bone tunnels in groups A and B, HE staining and Masson staining to observe the regeneration of fibrocartilage at the tendon-bone interface after decalcification and sectioning, and Goldner trichrome staining to evaluate the calcification. Immunohistochemical staining was performed to detect the expressions of angiogenic factors, including vascular endothelial growth factor (VEGF) and bone morphogenetic protein 2 (BMP-2), as well as osteogenic factors at the tendon-bone interface. Additionally, immunofluorescence staining was used to examine the expressions of Arginase 1 and Integrin beta-2 to assess M1 and M2 macrophage polarization at the tendon-bone interface. The role of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway in tendon-bone healing was further analyzed using real-time fluorescence quantitative PCR. RESULTS: Analysis of visceral sections revealed that magnesium ions released during the degradation of magnesium alloys did not cause significant toxic effects on organs such as the heart, liver, spleen, lungs, and kidneys, indicating good biosafety. Histological analysis further demonstrated that fibrocartilage regeneration at the tendon-bone interface in group A occurred earlier, and the amount of fibrocartilage was significantly greater compared to group B, suggesting a positive effect of magnesium alloy material on tendon-bone interface repair. Additionally, Micro-CT analysis results revealed that bone tunnel formation occurred more rapidly in group A compared to group B, further supporting the beneficial effect of magnesium alloy on bone healing. Biomechanical testing showed that the ultimate load in group A was consistently higher than in group B, and the stiffness of group A was also greater than that of group B at 4 weeks, indicating stronger tissue-carrying capacity following tendon-bone interface repair and highlighting the potential of magnesium alloy in enhancing tendon-bone healing. Immunohistochemical staining results indicated that the expressions of VEGF and BMP-2 were significantly upregulated during the early stages of healing, suggesting that magnesium alloy effectively promoted angiogenesis and bone formation, thereby accelerating the tendon-bone healing process. Immunofluorescence staining further revealed that magnesium ions exerted significant anti-inflammatory effects by regulating macrophage polarization, promoting their shift toward the M2 phenotype. Real-time fluorescence quantitative PCR results demonstrated that magnesium ions could facilitate tendon-bone healing by modulating the PI3K/AKT signaling pathway. CONCLUSION Biodegradable magnesium alloy material accelerated fibrocartilage regeneration and calcification at the tendon-bone interface in rat rotator cuff tear repair by regulating the PI3K/AKT signaling pathway, thereby significantly enhancing tendon-bone healing.
Animals ; Rotator Cuff Injuries/metabolism* ; Rats, Sprague-Dawley ; Signal Transduction ; Wound Healing/drug effects* ; Alloys/pharmacology* ; Rats ; Proto-Oncogene Proteins c-akt/metabolism* ; Rotator Cuff/metabolism* ; Macrophages/metabolism* ; Magnesium/pharmacology* ; Phosphatidylinositol 3-Kinases/metabolism* ; Vascular Endothelial Growth Factor A/metabolism* ; Male ; Biocompatible Materials ; Bone Morphogenetic Protein 2/metabolism*

The development and validation of clinical prediction models based on artificial intelligence (AI) and machine learning methods have become increasingly widespread. However, the prediction model bias risk and applicability evaluation tool developed in 2019 (i.e., PROBAST-2019) has shown significant limitations. Therefore, an expanded and updated version of the PROBAST-2019 tool was released in 2025, known as the PROBAST+AI tool. The tool is divided into two parts including model development and model evaluation. It aims to comprehensively and systematically evaluate potential methodological quality issues in model development, bias risks in model evaluation, and the applicability of models, regardless of the modeling method used. This paper provides a systematic interpretation of the PROBAST+AI tool's items and case analyses, with the aim of guiding and assisting researchers engaged in related studies and promoting the high-quality development of clinical predictive model research.

Objective To construction of discharge readiness assessment index for patients with percutaneous transhepatic biliary drainage.Methods Based on the framework of the Meleis's transitions theory,the relevant literature was consulted,the semi-structured interview and group discussion were implemented,and the framework of the assessment index system for discharge readiness of patients with percutaneous transhepatic biliary drainage was initially constructed.Then,two rounds of Delphi expert consultations were conducted.The weight of each indicator was set by Analytic Hierarchy Process.Results The effective recovery of 2 rounds of expert consultations were both 100％.The authority coefficients were 0.964 and 0.972,The Kendall harmony coefficients were 0.240 and 0.228(P＜0.001).The final discharge readiness assessment index system for patients with percutaneous transhepatic biliary drainage was established,including 4 first-level indicators and 35 second-level indicators.Conclusion The discharge readiness assessment index system for patients with percutaneous transhepatic biliary drainage was scientific and reliable,which can provide references for the evaluation of discharge readiness for patients with percutaneous transhepatic biliary drainage.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

This paper summarized professor WANG Shouchuan's experience in differentiating and treating children epistaxis from the perspective of "four excess and three deficiency". It is believed that the pathogenesis of children epistaxis is concluded as "four excess and three deficiency"， of which the four excess syndromes are exuberant heat in the lung channel， intense stomach fire， heart fire hyperactivity， and liver fire flaming upward， while the three deficiency syndromes include qi， yin and yang deficiency. Seven methods for treating children epistaxis are summarized. For exuberant heat in the lung channel syndrome， it is recommended to clear lung and direct qi downward， using self-made Xiebai Zhiniu Decoction （泻白止衄汤）. For intense stomach fire syndrome， the method of clearing stomach and draining fire can be used with self-made Qingwei Zhiniu Decoction （清胃止衄汤）. In terms of heart fire hyperactivity syndrome， it is better to clear heart and drain fire， using self-made Daochi Zhiniu Decoction （导赤止衄汤）. For liver fire flaming upward syndrome， it is advised to clear liver and drain fire， using self-made Yimu Zhiniu Decoction （抑木止衄汤）. In terms of qi deficiency syndrome， the method of fortifying spleen and boosting qi and containing blood should be used with self-made Futu Zhiniu Decoction （扶土止衄汤）. If there is yin deficiency syndrome， it is advised to supplement kidney， enrich yin and clear heat， using self-made Zishui Zhiniu Decoction （滋水止衄汤）. If there is yang deficiency syndrome， the method of boosting qi， warming yang and nourishing blood can be used， using self-made Wenpi Zhiniu Decoction （温脾止衄汤）.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.

Objective To analyse the characteristics of spatial distribution of bed resources and bed utilization efficiency of various types of medical and health institutions in Guangxi Province in 2018-2022,and to provide a reference basis for the allocation and management of bed resources of various types of medical and health institutions.Methods Spatial autocorrelation was used to analyse the status of bed allocation in various types of medical and health institutions,and the bed efficiency index and bed utilisation model were used to evaluate the efficiency of bed utilisation.Results Bed resources per 1 000 population vary considerably across types of healthcare organisations and regions.There is no spatial correlation in the overall distribution of bed resources per 1 000 population,but there are different types of aggregation,and there will be little change in the type of aggregation and the place of aggregation from 2018 to 2022.In terms of utilisation efficiency,the bed efficiency index of maternity and child healthcare hospitals is the highest,the bed efficiency index of specialist disease prevention and treatment hospitals(institutes and stations)is the lowest,general hospitals and maternity and child healthcare hospitals are operating at high efficiency,and all other healthcare institutions are operating at low efficiency;the utilisation of bed resources in various types of healthcare institutions exists in the form of efficiency-type,turn-around-type,bed-pressure-type,and unused-type hospitals at the same time.Conclusion There is an imbalance in the allocation of bed resources in various types of medical and health institutions,with large differences in the operational and utilisation efficiencies of beds;the allocation of bed resources should be continuously optimised.