Objective To develop a decision support system for clinical nursing plans based on nursing diagno-sis and explore its application effects,in order to provide references for optimizing the clinical nursing process and improving the quality of nursing.Methods A multidisciplinary research team was established to construct a clini-cal nursing plan decision support system framework from 3 aspects,namely nursing diagnosis,nursing interventions,and outcome tracking.The system built a clinical nursing diagnosis decision knowledge base through 3 dimensions,namely basic nursing diagnoses,specialty disease nursing diagnoses,and nursing-related technical diagnoses.Deep learning-based artificial intelligence capture technology was developed to achieve intelligent matching and generate clinical nursing plan forms.Implemented in a tertiary hospital in Yichang City,Hubei Province,a control group(June to August 2024)and an experimental group(October to December 2024)were compared regarding nursing diagnosis implementation rate,nursing plan documentation accuracy,and clinical nursing quality scores.Results This research showed a significant improvements for nursing diagnosis implementation rate increased from 94.88％to 97.25％,and nursing plan documentation accuracy improved from 90.38％to 95.33％.Compared with the control group,the experimental group demonstrated statistically significant enhancements in deep vein thrombosis preven-tion,fall prevention,pressure injury management,unplanned extubation control,bloodstream infection control,catheter-related infection prevention,and key specialty nursing quality indicators(all P＜0.05).Conclusion The nursing di-agnosis-based clinical decision support system effectively improves nurses'diagnostic implementation rates,enhances documentation accuracy of nursing plans,and elevates overall clinical nursing quality.

Objective To develop a decision support system for clinical nursing plans based on nursing diagno-sis and explore its application effects,in order to provide references for optimizing the clinical nursing process and improving the quality of nursing.Methods A multidisciplinary research team was established to construct a clini-cal nursing plan decision support system framework from 3 aspects,namely nursing diagnosis,nursing interventions,and outcome tracking.The system built a clinical nursing diagnosis decision knowledge base through 3 dimensions,namely basic nursing diagnoses,specialty disease nursing diagnoses,and nursing-related technical diagnoses.Deep learning-based artificial intelligence capture technology was developed to achieve intelligent matching and generate clinical nursing plan forms.Implemented in a tertiary hospital in Yichang City,Hubei Province,a control group(June to August 2024)and an experimental group(October to December 2024)were compared regarding nursing diagnosis implementation rate,nursing plan documentation accuracy,and clinical nursing quality scores.Results This research showed a significant improvements for nursing diagnosis implementation rate increased from 94.88％to 97.25％,and nursing plan documentation accuracy improved from 90.38％to 95.33％.Compared with the control group,the experimental group demonstrated statistically significant enhancements in deep vein thrombosis preven-tion,fall prevention,pressure injury management,unplanned extubation control,bloodstream infection control,catheter-related infection prevention,and key specialty nursing quality indicators(all P＜0.05).Conclusion The nursing di-agnosis-based clinical decision support system effectively improves nurses'diagnostic implementation rates,enhances documentation accuracy of nursing plans,and elevates overall clinical nursing quality.

Objective:This study aims to systematically sort out the effectiveness evaluation of the general education teaching models in epidemiology at home and abroad and provide a reference for the development and reform of epidemiology education.Methods:A systematic search of English databases such as PubMed, Embase, and Web of Science and Chinese databases such as CNKI, Sinomed, Wanfang, etc., were used to screen out the literature on different general teaching models of education in epidemiology. Each literature's teaching effect will be summarized and evaluated to conduct a systematic qualitative review in the narrative integration method, Results:A total of 45 articles (28 in Chinese and 17 in English) were included in this study, involving 14 teaching models, including mixed teaching models, PBL (problem-based learning), project designing models, and CBL (case-based learning) and other teaching models. Except for some teaching models such as project design, network platform, and flipped classroom model, the teaching effect of other innovative models is better than that of the traditional model. The distribution of teaching models was different in Chinese and foreign literature. Foreign teaching models were diverse, mainly concentrated in mixed teaching models and software/network platform learning. Domestic teaching models were relatively fixed. The mixed teaching model and PBL model were the most widely used in China, and there were fewer comparative studies between different teaching models than in foreign countries.Conclusion:General education in epidemiology is still in the early exploration stage. Compared with the traditional lecture model, the effect of various innovative teaching models has been improved. According to teaching objectives and student characteristics, we encourage extensive use of different teaching strategies, combining theoretical knowledge with practical applications and integrating epidemiological knowledge with inter-professional knowledge. Thus, students who can apply what they learn are becoming interdisciplinary talents our society needs.

Objective To investigate the clinical effect of Paclitaxel and Cisplatin(TP) combined with radiotherapy and clinical security in advanced local cervical cancer. Methods After informed consent,80 patients with cervical canco were studied prospectively,and divided into TP combined with radiotherapy group(40 cases,observation group) ,and surgery group(40 cases,control group). The clinical effect and adverse reactions were analyzed. Results Total effective rate in study group was 80. 0% ,50. 0% in control group,the difference showed statistical significance(x2 =3.47,P ＜0.05).The transfer rate of pelvis lymph node was 5. 0% in observation group,22. 5% in control group, the difference showed statistical significance( x2 = 4. 78 ,P ＜ 0. 05). The difference of adverse reactions between two groups showed no statistical significance( P ＞ 0. 05). Conclusion Clinical effect of Paclitaxel and Cisplatin combined with radiotherapy was obvious in advanced local cervical cancer patients,with little side effect,and could be applied to clinical practice.