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| 1 | Clinical Study on the Treatment of Low Anal Fistula in Infants and Young Children by Anal Gland Excision and Virtual Hanging Procedure显示文摘Objective:To compare the efficacy of anal adenectomy with virtual hanging wire and anal fistulotomy in the treatment of low anal fistula in infants and children.Methods:60 children with low anal fistula who were admitted to our hospital from October 2021 to March 2022 and met the inclusion criteria were randomly divided into two groups of 30 cases each;the treatment group was treated with anal adenectomy and virtual hanging wire surgery,and the control group was treated with anal fistula resection.The clinical efficacy after treatment was compared.Results:The total effective rate of both groups was 96.67%and the difference between the two groups was not statistically significant(P>0.05).The postoperative pain score of the treatment group was lower than that of the control group(P<0.05).The length of hospitalization and healing time of the treatment group was lower than that of the control group(P<0.05).The anal function of the patients in both groups was normal,and there was no adverse reaction.Conclusion:Anal gland excision and virtual hanging surgery for the treatment of low anal fistula in infants and children have the advantages of mild pain,reduced length of hospitalization,short healing time,and better patient experience as compared to anal fistula excision. | Hongbo Su Linmei Sun Yimiao Liang Jiansheng Hu Yongli Zhang Ni Wei Chaoyang Li Lin Tang | 2024 | Journal of Clinical and Nursing Research2024，8，3： | 0 |
| 2 | Personalized surgical recommendations and quantitative therapeutic insights for patients with metastatic breast cancer: Insights from deep learning显示文摘Background:The role of surgery in metastatic breast cancer(MBC)is currently controversial.Several novel statistical and deep learning(DL)methods promise to infer the suitability of surgery at the individual level.Objective:The objective of this study was to identify the most applicable DL model for determining patients with MBC who could benefit from surgery and the type of surgery required.Methods:We introduced the deep survival regression with mixture effects(DSME),a semi-parametric DL model integrating three causal inference methods.Six models were trained to make individualized treatment recommendations.Patients who received treatments in line with the DL models'recommendations were compared with those who underwent treatments divergent from the recommendations.Inverse probability weighting(IPW)was used to minimize bias.The effects of various features on surgery selection were visualized and quantified using multivariate linear regression and causal inference.Results:In total,5269 female patients with MBC were included.DSME was an independent protective factor,outperforming other models in recommending surgery(IPW-adjusted hazard ratio[HR]=0.39,95%confidence interval[CI]:0.19–0.78)and type of surgery(IPW-adjusted HR=0.66,95%CI:0.48–0.93).DSME was superior to other models and traditional guidelines,suggesting a higher proportion of patients benefiting from surgery,especially breast-conserving surgery.The debiased effect of patient characteristics,including age,tumor size,metastatic sites,lymph node status,and breast cancer subtypes,on surgery decision was also quantified.Conclusions:Our findings suggested that DSME could effectively identify patients with MBC likely to benefit from surgery and the specific type of surgery needed.This method can facilitate the development of efficient,reliable treatment recommendation systems and provide quantifiable evidence for decision-making. | Enzhao Zhu Linmei Zhang Jiayi Wang Chunyu Hu Qi Jing Weizhong Shi Ziqin Xu Pu Ai Zhihao Dai Dan Shan Zisheng Ai | 2024 | Cancer Innovation2024，3，3： | 0 |
| 3 | Entity set expansion in knowledge graph:a heterogeneous information network perspective显示文摘Entity set expansion(ESE)aims to expand an entity seed set to obtain more entities which have common properties.ESE is important for many applications such as dictionary con-struction and query suggestion.Traditional ESE methods relied heavily on the text and Web information of entities.Recently,some ESE methods employed knowledge graphs(KGs)to extend entities.However,they failed to effectively and fficiently utilize the rich semantics contained in a KG and ignored the text information of entities in Wikipedia.In this paper,we model a KG as a heterogeneous information network(HIN)containing multiple types of objects and relations.Fine-grained multi-type meta paths are proposed to capture the hidden relation among seed entities in a KG and thus to retrieve candidate entities.Then we rank the entities according to the meta path based structural similarity.Furthermore,to utilize the text description of entities in Wikipedia,we propose an extended model CoMeSE++which combines both structural information revealed by a KG and text information in Wikipedia for ESE.Extensive experiments on real-world datasets demonstrate that our model achieves better performance by combining structural and textual information of entities. | Chuan SHI Jiayu DING Xiaohuan CAO Linmei HU Bin WU Xiaoli LI | 2021 | Frontiers of Computer Science2021，15，1： | 0 |
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