Objective To discuss the method of constructing TCM word network and the subsequent optimization method;To solve the problems of natural language processing in the TCM-clinical decision support system using TCM terminology.Methods This study was based on several national standards and terminology dictionaries of TCM,such as Zhong Yi Lin Chuang Zhen Liao Shu Yu Ji Bing Part and Zhong Yi Yao Xue Zhu Ti Ci Biao,supplemented with related corpus on the Internet,and the framework of TCM word network was constructed with ontology as the guide.Word2Vec was used to load pre-trained models for similarity calculation,statistical and rule-based new word discovery,bibliometric analysis,and other methods to add or delete concept words and synonyms such as symptom terms and prescription terms.Results The TCM word network contained 55 semantic types and 13 semantic relationships,more than 110 000 concept words,and more than 300 000 synonyms.In addition to classifying concept words by semantic types,more detailed semantic classification was carried out in the upper and lower tree structures,in which more than 30 000 concept words had superordinate words,and nearly 2 600 concept words had subordinate words.At the same time,a process-based terminology supplementation mechanism,update review mechanism and cleaning mechanism were created.Conclusion TCM word network can not only be applied to the natural language processing process of TCM-clinical decision support system,but also can be applied to the normalization of data and the automatic construction of knowledge graph.

OBJECTIVE To investigate the characteristics of influenza A and influenza B viruses infections in the children aged between 0 and 14 years old after COVID-19 was downgraded to category B management of infectious diseases.METHODS From Jan.2023 to Feb.2024,a total of 2349 children aged between 0 and 14 years old who were treated in Beijing Hospital of Traditional Chinese Medicine,Capital Medical University due to influenza-like symptoms of infection and received nucleic acid testing for influenza A and influenza B viruses were recruited as the research subjects.The gender and age of the children as well as the seasons were observed by chi-square test.RESULTS Totally 2349 children were included in the study,and the total positive rate of influenza was 49.85％(1171/2349);the positive rate of influenza A virus was 36.36％(854/2349),the positive rate of influenza B virus was 13.92％(327/2349),and the positive rate of the mixed infections of influenza A virus and influenza B virus was 0.43％(10/2349).The positive rate of influenza A of the girls was the highest(44.17％)(x2=8.980,P=0.011)among the children aged less than 5 years old;the positive rate of influenza B of the boys was the highest(17.19％)(x2=8.378,P=0.015)among the children aged between 5 and 10 years old.There was significant difference in the positive rate of influenza A virus among the seasons in 2023 to 2024(x2=268.12,P＜0.001);the prevalence rate was 60.93％in spring,44.40％in autumn,22.01％in winter.There was significant difference in the positive rate of influenza B virus among the seasons in 2023 to 2024(x2=373.16,P＜0.001),and the preva-lence rate was 25.44％in winter.CONCLUSIONS The influenza viruses are prevalent in spring,autumn and winter from 2023 to 2024,and the influenza A is dominant.The positive rate of influenza viruses shows an upward trend among the children aged between 0 and 14 years old after the COVID-19 is downgraded to category B management of infectious diseases,with the peak of prevalence lagging behind.

Objective:To investigate relationship between IL-17/IL-23 immunoinflammatory axis and chronic heart failure(CHF)and clinical prognosis.Methods:A total of 112 patients with CHF in Chengde Central Hospital from January 2020 to Septem-ber 2021 were selected as observation group,and another 112 patients admitted to same period for healthy physical examination were selected as control group.Serum IL-17 and IL-23 levels of two groups were compared,relationship between serum IL-17 and IL-23 levels and degree of disease were analyzed;clinical data,serum IL-17 and IL-23 levels of patients with different prognosis were compared,relationship between serum IL-17 and IL-23 levels and clinical prognosis of CHF patients were analyzed.Predictive value of serum IL-17 and IL-23 levels on clinical prognosis of CHF patients was evaluated,and predictive value of each prediction scheme was compared.Results:Serum IL-17 and IL-23 levels were higher in observation group than control group(P<0.05);serum IL-17 and IL-23 levels of CHF patients were positively correlated with NYHA classification(P<0.05).Serum IL-17 and IL-23 levels were higher in patients with poor prognosis than in those with good prognosis(P<0.05).Serum IL-17 and IL-23 were independently associated with clinical prognosis of CHF patients,and the higher the serum IL-17 and IL-23 levels,the greater risk of poor clinical prognosis of CHF patients.AUC of serum IL-17 and IL-23 levels for predicting clinical prognosis of CHF patients were 0.787 and 0.726,respectively,and combined predicted AUC was 0.918(P<0.001);combined predicted AUC of serum IL-17 and IL-23 was significantly higher than single index(P<0.05).Conclusion:IL-17 and IL-23 levels in IL-17/IL-23 immunoinflammatory axis of CHF patients are significantly elevated and involve in disease occurence and development,whose clinical detection can help predict clinical prognosis of CHF.

OBJECTIVE To investigate the characteristics of influenza A and influenza B viruses infections in the children aged between 0 and 14 years old after COVID-19 was downgraded to category B management of infectious diseases.METHODS From Jan.2023 to Feb.2024,a total of 2349 children aged between 0 and 14 years old who were treated in Beijing Hospital of Traditional Chinese Medicine,Capital Medical University due to influenza-like symptoms of infection and received nucleic acid testing for influenza A and influenza B viruses were recruited as the research subjects.The gender and age of the children as well as the seasons were observed by chi-square test.RESULTS Totally 2349 children were included in the study,and the total positive rate of influenza was 49.85％(1171/2349);the positive rate of influenza A virus was 36.36％(854/2349),the positive rate of influenza B virus was 13.92％(327/2349),and the positive rate of the mixed infections of influenza A virus and influenza B virus was 0.43％(10/2349).The positive rate of influenza A of the girls was the highest(44.17％)(x2=8.980,P=0.011)among the children aged less than 5 years old;the positive rate of influenza B of the boys was the highest(17.19％)(x2=8.378,P=0.015)among the children aged between 5 and 10 years old.There was significant difference in the positive rate of influenza A virus among the seasons in 2023 to 2024(x2=268.12,P＜0.001);the prevalence rate was 60.93％in spring,44.40％in autumn,22.01％in winter.There was significant difference in the positive rate of influenza B virus among the seasons in 2023 to 2024(x2=373.16,P＜0.001),and the preva-lence rate was 25.44％in winter.CONCLUSIONS The influenza viruses are prevalent in spring,autumn and winter from 2023 to 2024,and the influenza A is dominant.The positive rate of influenza viruses shows an upward trend among the children aged between 0 and 14 years old after the COVID-19 is downgraded to category B management of infectious diseases,with the peak of prevalence lagging behind.

Objective To discuss the method of constructing TCM word network and the subsequent optimization method;To solve the problems of natural language processing in the TCM-clinical decision support system using TCM terminology.Methods This study was based on several national standards and terminology dictionaries of TCM,such as Zhong Yi Lin Chuang Zhen Liao Shu Yu Ji Bing Part and Zhong Yi Yao Xue Zhu Ti Ci Biao,supplemented with related corpus on the Internet,and the framework of TCM word network was constructed with ontology as the guide.Word2Vec was used to load pre-trained models for similarity calculation,statistical and rule-based new word discovery,bibliometric analysis,and other methods to add or delete concept words and synonyms such as symptom terms and prescription terms.Results The TCM word network contained 55 semantic types and 13 semantic relationships,more than 110 000 concept words,and more than 300 000 synonyms.In addition to classifying concept words by semantic types,more detailed semantic classification was carried out in the upper and lower tree structures,in which more than 30 000 concept words had superordinate words,and nearly 2 600 concept words had subordinate words.At the same time,a process-based terminology supplementation mechanism,update review mechanism and cleaning mechanism were created.Conclusion TCM word network can not only be applied to the natural language processing process of TCM-clinical decision support system,but also can be applied to the normalization of data and the automatic construction of knowledge graph.

Objective:To investigate relationship between IL-17/IL-23 immunoinflammatory axis and chronic heart failure(CHF)and clinical prognosis.Methods:A total of 112 patients with CHF in Chengde Central Hospital from January 2020 to Septem-ber 2021 were selected as observation group,and another 112 patients admitted to same period for healthy physical examination were selected as control group.Serum IL-17 and IL-23 levels of two groups were compared,relationship between serum IL-17 and IL-23 levels and degree of disease were analyzed;clinical data,serum IL-17 and IL-23 levels of patients with different prognosis were compared,relationship between serum IL-17 and IL-23 levels and clinical prognosis of CHF patients were analyzed.Predictive value of serum IL-17 and IL-23 levels on clinical prognosis of CHF patients was evaluated,and predictive value of each prediction scheme was compared.Results:Serum IL-17 and IL-23 levels were higher in observation group than control group(P<0.05);serum IL-17 and IL-23 levels of CHF patients were positively correlated with NYHA classification(P<0.05).Serum IL-17 and IL-23 levels were higher in patients with poor prognosis than in those with good prognosis(P<0.05).Serum IL-17 and IL-23 were independently associated with clinical prognosis of CHF patients,and the higher the serum IL-17 and IL-23 levels,the greater risk of poor clinical prognosis of CHF patients.AUC of serum IL-17 and IL-23 levels for predicting clinical prognosis of CHF patients were 0.787 and 0.726,respectively,and combined predicted AUC was 0.918(P<0.001);combined predicted AUC of serum IL-17 and IL-23 was significantly higher than single index(P<0.05).Conclusion:IL-17 and IL-23 levels in IL-17/IL-23 immunoinflammatory axis of CHF patients are significantly elevated and involve in disease occurence and development,whose clinical detection can help predict clinical prognosis of CHF.

Non-small cell lung cancer is one of the cancers with the highest incidence and mortality rate in the world, and precise prognostic models can guide clinical treatment plans. With the continuous upgrading of computer technology, deep learning as a breakthrough technology of artificial intelligence has shown good performance and great potential in the application of non-small cell lung cancer prognosis model. The research on the application of deep learning in survival and recurrence prediction, efficacy prediction, distant metastasis prediction, and complication prediction of non-small cell lung cancer has made some progress, and it shows a trend of multi-omics and multi-modal joint, but there are still shortcomings, which should be further explored in the future to strengthen model verification and solve practical problems in clinical practice.

ObjectiveThis study aimed to evaluate the clinical efficacy of Ruyi Zhenbaowan（RYZBW）in the treatment of initial and early knee osteoarthritis （KOA） through a prospective multicenter，randomized，double-blind，and placebo-parallel controlled trial. MethodFrom October 13^th， 2021 to December 25^th， 2021， 240 KOA subjects meeting the acceptance criteria were enrolled in 15 sub-centers including Wangjing Hospital， Chinese Academy of Chinese Medical Sciences， and they were randomly divided into observation group and control group， with 120 cases in each group. The intervention measures for the observation group were RYZBW + health education， and the intervention measures for the control group were RYZBW placebo + health education. The intervention period in both groups was four weeks， and they were followed up for four weeks after the intervention. The primary outcome measure was the total score of Western Ontario and McMaster University Osteoarthritis Index score （WOMAC score）， and the secondary outcome measures were the response rate of visual scale （VAS） pain score， WOMAC sub item scores （joint pain， joint stiffness， and joint function）， quality of life （SF-12） score， and traditional Chinese medicine （TCM） syndrome score. Result（1） Efficacy evaluation. The marginal model results showed that the observation group was better than the control group in improving the WOMAC total score and WOMAC pain score in the treatment of KOA with RYZBW， and the difference was statistically significant （P<0.05）. There was no significant difference between the two groups in improving VAS score response rate， WOMAC function score， WOMAC stiffness score， SF12-PCS （quality of life-physical health） score， SF12-MCS （quality of life-mental health） score， and TCM syndrome score. （2） Subgroup analysis. ① In terms of VAS score response rate， the response rate of the observation group was higher than that of the control group for subjects with baseline VAS score of （4， 5］， and the difference was statistically significant （P<0.05）. ② In terms of TCM syndrome score， for subjects aged ［56， 60］ and ［61， 65］， the decrease in total TCM syndrome score in the observation group was better than that in the control group， and the difference was statistically significant （P<0.05）. ConclusionTibetan medicine RYZBW has good clinical efficacy in improving WOMAC total score， VAS score response rate， WOMAC pain score， WOMAC function score， and TCM syndrome score for patients with initial and early KOA， which can fill the lack of Tibetan medicine RYZBW in the treatment of KOA and make a demonstration study for the inheritance and development of ethnic medicine.

Objective:To explore the efficacy of subcutaneous injection of granulocyte-macrophage colony-stimulating factor (GM-CSF) in preventing invasive fungal disease (IFD) in patients with multiple myeloma (MM).Methods:The clinical data of 222 patients who were admitted to the Second Hospital of Harbin Medical University from January 2015 to June 2021 were retrospectively analyzed. The patients was given GM-CSF (3-5 μg·kg -1·d -1, GM-CSF group) or granulocyte colony-stimulating factor (G-CSF, 2-5 μg·kg -1·d -1, G-CSF group) when neutrophils (ANC) ≤1.5×10 9/L after induction chemotherapy. Patients were discontinued when white blood cell count (WBC) ≥10.0×10 9/L. The incidence of IFD (including confirmed, clinical and proposed diagnosis) and breakthrough invasive fungal infections was compared between the two groups. Results:The incidence of IFD was 8.1% (18/222) in all patients. The incidence of IFD was 3.5% (3/85) and 10.9% (15/137) in the GM-CSF and G-CSF groups, respectively, and the difference between the two groups was statistically significant ( χ2 = 3.88, P = 0.049). In 9 patients of GM-CSF group receiving fungal infection prophylaxis and in 15 patients of G-CSF group receiving fungal infection prophylaxis, the incidence of breakthrough invasive fungal infections was 0 and 7 cases, respectively, and the difference between the two groups was statistically significant ( P = 0.022). Conclusions:GM-CSF application in MM patients can reduce the incidence of IFD and breakthrough invasive fungal infections.

Outpatient information management system is an important part of hospital information system,which plays an important role in hospital management,patient treatment,medical insurance reimbursement and settlement.This study integrated the application modes of big data,cloud computing,Internet of things and other cutting-edge technologies of artificial intelligence,focused on the intelligent decision support and whole-process simplified management of the diagnosis and treatment behavior of clinical TCM physicians,and developed a cloud intelligent TCM outpatient system for primary medical care.The system has intelligent medical functions such as intelligent prescription monitoring driven by the rule engine and intelligent recommendation of traditional Chinese medicine knowledge.It seamlessly connects with the intelligent four-diagnosis instrument for information collection and medical order input,and realizes the cloud storage,computing,distribution,management,service and outpatient process,multi-directional and convenient management mode.