Supervision Level Research Articles

An Intelligent Decision-Making Approach for Multi-Ship Traffic Conflict Mitigation from the Perspective of Maritime Surveillance

Potential multi-ship conflict situations in coastal or near-shore port areas have always been one of the important factors affecting ship navigation safety and a key target of maritime traffic regulatory authorities. In recent years, with the continuous development and integration of various emerging technologies in the maritime field, maritime traffic supervision has also shown a trend of intelligent and autonomous development. The traditional supervision method dominated by human experience is evolving towards data and model-driven practices. In order to solve the problem of ship navigation safety supervision under multi-ship conflict scenarios, it is urgent to build an intelligent conflict mitigation decision-making model. Therefore, this paper designs a novel risk mitigation decision-making model for multi-ship conflict scenarios from the perspective of maritime supervision. The model proposed in this paper first extracts high-density ship clusters based on AIS (Automatic Identification System) data and uses the MCD (Mean Core Density) and PRM (Proportion of Relative Motion) as feature indicators to further mine potential multi-ship conflict scenarios. Finally, a global optimization decision-making model is constructed to effectively mitigate conflict risks. Experimental verification shows that the intelligent decision-making model for the mitigation of maritime traffic conflict proposed in this paper can autonomously identify conflict scenarios and make reasonable decisions in real time. It can effectively ensure the navigation safety of ships in multi-ship conflict scenarios and further improve the supervision level of maritime departments.

Pathways to tourism eco-efficiency: fresh insights from a configuration perspective

ABSTRACT Balancing tourism growth with environmental pressures is an urgently needed complex issue. Tourism eco-efficiency (TEE) has become an important tool for addressing this challenge. We use complexity theory to understand the intricacies of improving TEE, focusing on data from 30 Chinese provinces from 2011 to 2019, and introduce a configurational perspective to this field. The following conclusions are drawn: Firstly, we innovatively propose the Government-Market-Public-Technical (GMPT) framework, which distills six conditions: government supervision, government attention, market competition, market liberalisation, public supervision, and digital level. Secondly, TEE has steadily increased, regional disparities have narrowed, and the spatial pattern has shifted from ‘multi-core’ dispersion to ‘block’ aggregation. Thirdly, unlike existing research on TEE, there is no symmetrical causal relationship between GMPT and TEE. Moreover, a single GMPT condition is not necessary for high or low TEE levels. We also innovatively summarise the combinatorial paths. Four types of condition combinations can produce high-level TEE, including Market liberalization Tech Driven, Government-Market Dual Interaction Tech-Driven, Government-Public Dual Interaction Tech-Driven, and Government-Market-public-Tech Driven Coordinated Type. We identify three types of deficiency elements that impede TEE enhancement. This study provides important theoretical and practical insights for promoting eco-tourism and achieving high-quality tourism development under sustainable conditions.

Research on risk data analysis of hazardous chemical vessels based on stream computing

Abstract To effectively improve the safety supervision and information management level of vessels carrying hazardous chemicals, the maritime management department is promoting the construction of hazardous chemical vessel monitoring systems based on artificial intelligent technology for hazardous chemical terminals and shipping companies in their jurisdiction. It can identify specific risks and transmit the risk data in real-time to the data center. To analyze data in real-time, a risk data analysis platform for hazardous chemical vessels based on stream computing is designed and implemented. The platform acquires vessel automatic identification system (AIS), risk, basic information, and other data. Based on the stream computing of Flink, it evaluates the risk status of vessels in real time, counts the risk data, and displays the results in the form of charts. The analysis of risk data for hazardous chemical vessels helps maritime management departments to track the real-time navigation status of key vessels, timely identify potential safety hazards, and effectively improve the level and efficiency of safety supervision.

Primary caregiver employment status is associated with traumatic brain injury in children in the USA

BackgroundTraumatic brain injury (TBI) is a common injury in children. Previous literature has demonstrated that TBI may be associated with supervision level. We hypothesised that primary caregiver employment would be...

Gait training with a safety suspension device accelerates the achievement of supervision level walking in subacute stroke: a randomized controlled trial.

Practicing walking in a safety suspension device allows patients to move freely and without excessive reliance on a therapist, which requires correcting errors and may facilitate motor learning. This opens the possibility that patients with subacute stroke may improve their walking ability more rapidly. Therefore, we tested the hypothesis that overground gait training in a safety suspension device will result in achieving faster supervision-level walking than gait training without the suspension device. Twenty-seven patients with stroke admitted to the rehabilitation ward with functional ambulation categories (FAC) score of 2 at admission were randomly allocated to safety suspension-device group (SS group) or conventional assisted-gait training group (control group). In addition to regular physical therapy, each group underwent additional gait training for 60 min a day, 5 days a week for 4 weeks. We counted the days until reaching a FAC score of 3 and assessed the probability using Cox regression models. The median days required to reach a FAC score of 3 were 7 days for the SS group and 17.5 days for the control group, which was significantly different between the groups ( P < 0.05). The SS group had a higher probability of reaching a FAC score of 3 after adjusting for age and admission motor impairment (hazard ratio = 3.61, 95% confidence interval = 1.40-9.33, P < 0.01). The gait training with a safety suspension device accelerates reaching the supervision-level walking during inpatient rehabilitation. We speculate that a safety suspension device facilitated learning by allowing errors to be experienced and correct in a safe environment.

Design of Safety Evaluation and Risk Traceability System for Agricultural Product Quality

The quality and safety of agricultural products involve a variety of risk factors, a large amount of risk information data, and multiple circulation and disposal processes, making it difficult to accurately trace the source of risks. To achieve precise traceability of agricultural product quality and safety, the monitoring and supervision level of agricultural product traceability systems needs to be improved. In this paper, the agricultural product quality- and safety-related detection data are taken as the research object, the agricultural product supply chain and business process are sorted out, the agricultural product risk factors under the influence of heavy metals are analyzed, and the agricultural product quality and safety risk evaluation model is established. The agricultural product risk traceability system was designed based on the six-layer architecture of the equipment layer, data layer, service layer, application layer, display layer, and user layer. Combined with the agricultural product quality and safety risk evaluation model, the system data were stored and modified by using the MySQL relational database, and the agricultural product risk traceability system was developed, which realized the accurate traceability of the risk link of the quality and safety of agricultural products. The research results of this paper provide an effective information means for the quality and safety supervision of agricultural products, and provide a technical reference for the development of a traceability system of risk factors related to agricultural products, which has good practical significance.

Semi-supervised learning towards automated segmentation of PET images with limited annotations: application to lymphoma patients.

Manual segmentation poses a time-consuming challenge for disease quantification, therapy evaluation, treatment planning, and outcome prediction. Convolutional neural networks (CNNs) hold promise in accurately identifying tumor locations and boundaries in PET scans. However, a major hurdle is the extensive amount of supervised and annotated data necessary for training. To overcome this limitation, this study explores semi-supervised approaches utilizing unlabeled data, specifically focusing on PET images of diffuse large B-cell lymphoma (DLBCL) and primary mediastinal large B-cell lymphoma (PMBCL) obtained from two centers. We considered 2-[18F]FDG PET images of 292 patients PMBCL (n = 104) and DLBCL (n = 188) (n = 232 for training and validation, and n = 60 for external testing). We harnessed classical wisdom embedded in traditional segmentation methods, such as the fuzzy clustering loss function (FCM), to tailor the training strategy for a 3D U-Net model, incorporating both supervised and unsupervised learning approaches. Various supervision levels were explored, including fully supervised methods with labeled FCM and unified focal/Dice loss, unsupervised methods with robust FCM (RFCM) and Mumford-Shah (MS) loss, and semi-supervised methods combining FCM with supervised Dice loss (MS + Dice) or labeled FCM (RFCM + FCM). The unified loss function yielded higher Dice scores (0.73 ± 0.11; 95% CI 0.67-0.8) than Dice loss (p value < 0.01). Among the semi-supervised approaches, RFCM + αFCM (α = 0.3) showed the best performance, with Dice score of 0.68 ± 0.10 (95% CI 0.45-0.77), outperforming MS + αDice for any supervision level (any α) (p < 0.01). Another semi-supervised approach with MS + αDice (α = 0.2) achieved Dice score of 0.59 ± 0.09 (95% CI 0.44-0.76) surpassing other supervision levels (p < 0.01). Given the time-consuming nature of manual delineations and the inconsistencies they may introduce, semi-supervised approaches hold promise for automating medical imaging segmentation workflows.

The Adequacy of Health System Measures in Reducing Vulnerability to COVID-19 Among the Health Care Providers Working in Primary Health Care in Rajasthan, India: A Cross-sectional Study

This article examines the role of individual, facility and system-level preparedness in reducing physiological and psychological vulnerability among primary-level health care providers (HCPs) during the COVID-19 pandemic in Rajasthan, India. Online and telephonic interviews are conducted among 274 HCPs working in 24 primary health centres (PHCs) (17 rural and 7 urban) across 13 districts of Rajasthan. Five dimensions of vulnerability, covering awareness, exposure to infection (daily contact; contact with high-risk individuals), physical and mental health conditions, while three aspects of preparedness—at individual (personal care) and facility (provider safety; management and supervision) level—are measured by employing factor analysis. Generalised ordered logit regression model is used to measure the effect of preparedness on COVID-19-related vulnerability. Among the 274 HCPs, majority of the staff are from rural PHCs (76%), less than 35 years old (87%), female (57%) and married (57%). Almost half have high level of exposure to COVID-19, with mean contact rate of 90. Overall, 26% have comprehensive knowledge of COVID-19, and 32% have any mental health issues. Although more than 70% of HCPs have reported more than one individual-level preparedness, mental health measures adopted by the HCPs are comparably low. The facility-level preparedness for enhancing safety is high such as social distancing (79%) and maintaining record of each visitor (75%). However, management-related measures adopted by the PHCs are perceived to be lower than the safety measures. The regression analyses suggest that safety-related preparedness is significantly associated with reduction of vulnerability by 50%. The management-level preparedness has statistically no significant effect in explaining the variations in level of vulnerability. The facility-level safety measures, which lower chances of acquiring infection, have a positive effect on reducing vulnerability to COVID-19. However, the HCPs do not have adequate preparedness at individual, facility management (PHC) and system levels to reduce COVID-19 vulnerability. Findings suggest that there is a need for a non-conventional approach of monitoring and supervision. In the absence of such measures, there is a chance of moral injury that will make the HCPs at the primary level vulnerable both physiologically and psychologically.

Examining the Applicability of Surgical Coaching Rules for Resident Autonomy in Non-teaching Hospitals.

This retrospective study aims to analyze the impact of standardized rules for teaching in university hospitals on surgical resident autonomy and patient safety, as measured by patient outcomes, and also examines the learning curves for residents and their impact on patient outcomes in a non-teaching hospital. The data for the study was collected retrospectively from medical records of 2000 adult patients who went through surgical procedures fromJanuary 2020 to December 2022. Participants were categorized into two groups based on the supervision level provided by attending surgeons and residents. Appropriate statistical methods were used to analyze the data. It was observed that operative times of cases handled by both attending and resident surgeons were less than those handled by residents alone. On the other hand, the former group had a significantly higher burden of comorbidities and higher rate of perioperative complications than the latter. These results have important implications for the training of medical residents and the overall delivery of healthcare services in university hospitals. The findings will also help towards better understanding of the effectiveness of these rules and their potential for improving the quality of care provided by residents in these settings.

One-Leg Robotic-Assisted Gait Training Efficiently Improves Gait Independence for Acute Stroke Hemiplegic Patients: A Prospective Pilot Study.

Welwalk is a one-leg robotic-assisted gait system for stroke hemiplegic patients. This study examined the feasibility and efficacy of gait training using Welwalk (Welwalk training) for hemiplegic patients in the early phase after stroke onset, via cooperation between acute care and rehabilitation hospitals. Seven acute stroke patients (mean number of days from onset = 7.9) with severe lower extremity paralysis participated. Patients underwent Welwalk training for 40 min/d, 5 d/wk in an acute care hospital, then 7 d/wk in a rehabilitation hospital with a seamless transition. Functional Independence Measure scores for walking were assessed weekly. The endpoint was reaching Functional Independence Measure walk score of 5 (supervision level). The primary outcome was improvement efficiency of Functional Independence Measure walk, which was the increase in Functional Independence Measure walk score divided by the number of weeks required. Functional Independence Measure walk score for all patients improved from 1.1 to 5 ( P = 0.01, r = 0.96). The mean number of weeks to achieve Functional Independence Measure walk score of 5 was 5 wks, and the improvement efficiency of Functional Independence Measure walk had a mean value of 0.9. No adverse events were reported during Welwalk training. Hemiparetic patients' gait independence may be safely and rapidly improved by starting Welwalk training in the early phase after stroke onset.

Penerapan Acceptable Quality Level (AQL) Dalam Tahapan Final Inspection Produk Garmen Di PT XYZ

Quality control in the garment industry plays an important role to ensure that the products produced meet high quality standards and satisfy consumers. The Acceptable Quality Level method is a promising approach for optimizing garment product control. This research focuses on the application of the Acceptable Quality Level method in managing garment quality at PT XYZ. The aim is to explore the extent to which this method can be applied efficiently in garment production by considering the existing challenges and opportunities. This study uses the "L Tunic Crinckle" tunic sample from PT XYZ as the research object. Data collection involves primary data from direct interactions and observations, as well as secondary data from related literature and journals. Raw material sampling methods are based on product defects, focusing on attribute data to assess non-compliance with specifications. With an AQL value of 2.5% and general supervision level II, this study took a sample of 125 tunics for inspection. Even though several minor and major defects were found, the total rejects did not exceed acceptance standards, so the tunic product lot could be accepted without re-inspection

Designing Entrustable Professional Activities for Treatment Planning of Oral Cancer by Maxillofacial Surgery Residents: A Modified Delphi Study.

The aim of this study was to develop a competency framework based on entrustable professional activities (EPAs) in oral cancer management by postgraduate trainees in oral and maxillofacial surgery through expert consensus. The study design was based on a modified Delphi technique and involved iterative online surveys with two rounds of data collection and analysis. Initial development of the questionnaire identified five EPAs based on 42 competencies along with supervision level and assessment strategies. The first Delphi round involved administration of the survey questionnaire online to maxillofacial surgeons meeting the inclusion criteria for experts. Consensus was achieved on five EPAs and 36 competencies (≥80% response rate). Six competencies were rephrased and sent again in the Round 2 questionnaire to achieve a consensus. A total of 45 experts participated in Round 1 followed by input from 27 experts in Round 2 of the Delphi panel. Following two iterative rounds of online surveys and feedback, expert consensus was achieved to develop an EPA framework in five EPA domains focused on the management of oral cancer by postgraduate trainees in maxillofacial surgery including 38 specific competencies, supervision level, and assessment strategies. High content validity of the study was established through a comprehensive literature search, and expert feedback was evidenced by an excellent response rate (93.34%, and 64.28%) and a stringent criteria of response agreement amongst experts (≥80%). In conclusion, this study employed expert consensus to identify five EPAs with 38 competencies along with the required supervision level of postgraduate maxillofacial trainees for the management of oral cancer. This EPA framework provides a roadmap for training supervisors to map the learning outcomes in oral oncology for postgraduate trainees in oral and maxillofacial surgery.

Pricing strategy of knowledge payment products considering copyright supervision in the blockchain technology era

PurposeThe purpose of this study is to investigate the pricing strategies for knowledge payment products, taking into account the quality level of pirated knowledge products, in the context of platform copyright supervision.Design/methodology/approachThis study abstracts the knowledge payment transaction process and aims to maximize producer's revenue by constructing a pricing model for knowledge payment products. It discusses pricing strategies for knowledge payment products under two scenarios: traditional supervision and blockchain supervision. The analysis explores the impact of pirated knowledge products quality level and blockchain technology on pricing strategies and consumer surplus, while providing threshold conditions for effective strategies.FindingsDeploying blockchain technology in platform operations can significantly reduce costs and increase efficiency. In both scenarios, knowledge producer needs to balance factors such as the quality of pirated knowledge products, the supervision level of platform, and consumer surplus to dynamically adjust pricing strategies in order to maximize his own revenue.Originality/valueThis study enriches the literature on the pricing models of knowledge payment products and has practical significance in guiding knowledge producer to develop effective pricing strategies under copyright supervision.

The Future of Chemotherapy: The Mechanisms and Benefits of Exercise in Taxane-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a dose-limiting side-effect resulting from numerous neurotoxic chemotherapies that damages the peripheral nerves, alters sensations in the hands and feet, causes burning and shooting pains, and impairs a patient’s quality of life (QoL). There are limited established interventions to help improve CIPN symptoms. There is only one pharmacological agent (Duloxetine) for treatment of CIPN; however, it only has mild benefit, signaling a critical need for alternative management options to manage patient symptoms. Multiple studies suggest therapeutic benefits of exercise in cancer care to improve physical and psychological functioning; however, the benefits regarding CIPN symptoms and physical function are less clear. This narrative review synthesizes research articles investigating the effect and mechanisms induced by different exercise programs for patients with taxane-induced peripheral neuropathy (TIPN) symptoms and function. The overall incidence, manifestations, characteristics, and mechanisms of CIPN are also discussed. While some studies in this narrative review demonstrated that exercise programs may have benefits on sensory and motor TIPN symptoms in some but not all patients, there are consistent benefits of improved QoL and physical function across most patients. This narrative review highlights the need for future research to confirm the effects of exercise for TIPN, with a focus on other important components, including the effect of exercise adherence, type, and supervision level.

Developing the Urban Fire Safety Co-Management System in China Based on Public Participation

The new situations, problems, and challenges facing urban fire safety work are gradually increasing in China, so innovating urban fire safety governance modes is an urgent task. In the fire management practice of the Chinese government, the establishment of an urban fire safety co-management system is an important measure for aggregating fire safety management resources and improving the level of urban fire safety prevention, as well as control. In order to reveal and clarify the interacting relationships and influencing mechanisms among multiple subjects in an urban fire safety co-management system, we constructed an urban fire safety co-management game model comprising fire supervision departments, production management units, and the public based on evolutionary game theory. The stability of the urban fire safety co-management game system is explored from the perspective of game subjects. The influencing factors of strategy selection between game subjects in the game system were investigated using numerical simulation analysis. The research results show that elevating the informatization level of co-management, the risk perception level of the public, and the disclosure level of fire safety information are conducive to stimulating the public’s positivity to participate in co-management. Strengthening the accountability of the superior government is conducive to ensuring the supervision level of fire supervision departments. The above measures have positive value for optimizing China’s urban fire safety co-management systems, establishing urban fire safety management synergy, and ensuring the stability of social fire safety situations.

Application of Quality Inspection Data Association Rules in Measurement Terminal Based on MapReduce

To solve the problem of not being able to intuitively lock the cause of defects when processing massive quality inspection datasets with multiple batches, types, and models of measurement terminals, a MapReduce-based Apriori algorithm is proposed. After the MapReduce algorithm model calculation, the processing efficiency of the quality inspection dataset has been significantly improved. Through the multi-node calculation and analysis of the single-phase electricity meter quality inspection dataset and the application of association rule mining, reasonable suggestions were given, which improved the professional value and quality supervision level of the quality inspection business.

Effects of aerobic, resistance, and combined exercise training on health-related quality of life in multiple sclerosis: Systematic review and meta-analysis.

Multiple sclerosis (MS) is an immune-mediated, neurodegenerative disease of the central nervous system that manifests in symptoms that compromise health-related quality of life (HRQOL). HRQOL focuses on a person's overall, subjective evaluation of health status primarily in the physical and mental domains. Exercise training is a form of rehabilitation for managing MS-related outcomes that might influence HRQOL. Reviews on exercise training are available, but we are unaware of a recent comprehensive review and meta-analysis of exercise effects for improving physical and mental domains of HRQOL. This analysis provides an updated review and meta-analysis of randomized controlled trials (RCTs) examining interventions consisting of aerobic, resistance and combined exercise training for improving HRQOL in persons with MS. This systematic review 1) assessed the overall strength of evidence for exercise interventions on HRQOL, 2) evaluated the relative effect of exercise interventions on physical and mental domains of HRQOL, and 3) determined moderators of exercise intervention effects on HRQOL. Seven databases were searched for RCTs evaluating physical and/or mental domains of HRQOL with adults diagnosed with MS and undergoing an intervention of aerobic, resistance or combined exercise training compared with a non-exercise comparator. Data extraction included participant and intervention characteristics, and pre- and post-intervention HRQOL outcome data. Effect sizes (ESs) were calculated as standardized mean differences (SMDs) and a multilevel random-effects model was used to generate an aggregated SMD that compared exercise with non-exercise control conditions. Twelve RCTs met the inclusion criteria and yielded 23 ESs to be analyzed. Participants (N=593; 308 intervention vs. 285 control conditions) had a mean (±standard deviation) age of 42.4 (6.5) years and 80% (18.3%) were female. Results generated a medium effect of exercise for improving overall HRQOL (ES=0.64, p=0.0001) with high heterogeneity (Q11=58.8, I2=86.7%). Exercise training yielded a large effect on the physical domain (k=12, ES=0.82, p<0.0009) and a medium effect on the mental domain (k=11, ES=0.41, p<0.0001). Moderator analyses identified exercise modality, supervision level, intervention delivery and length, HRQOL tool, and number of participants with relapsing-remitting MS as significant influences of ES for HRQOL. Exercise training is clinically effective for improving overall HRQOL in MS and produces greater improvements in the physical domain of HRQOL than the mental domain. The moderator analysis suggests that supervised, aerobic, and group-delivered exercise training of ≥3 months yields the most influence on HRQOL. Such results may have major implications for MS treatment and care.

FedMix: Mixed Supervised Federated Learning for Medical Image Segmentation.

The purpose of federated learning is to enable multiple clients to jointly train a machine learning model without sharing data. However, the existing methods for training an image segmentation model have been based on an unrealistic assumption that the training set for each local client is annotated in a similar fashion and thus follows the same image supervision level. To relax this assumption, in this work, we propose a label-agnostic unified federated learning framework, named FedMix, for medical image segmentation based on mixed image labels. In FedMix, each client updates the federated model by integrating and effectively making use of all available labeled data ranging from strong pixel-level labels, weak bounding box labels, to weakest image-level class labels. Based on these local models, we further propose an adaptive weight assignment procedure across local clients, where each client learns an aggregation weight during the global model update. Compared to the existing methods, FedMix not only breaks through the constraint of a single level of image supervision but also can dynamically adjust the aggregation weight of each local client, achieving rich yet discriminative feature representations. Experimental results on multiple publicly-available datasets validate that the proposed FedMix outperforms the state-of-the-art methods by a large margin. In addition, we demonstrate through experiments that FedMix is extendable to multi-class medical image segmentation and much more feasible in clinical scenarios. The code is available at: https://github.com/Jwicaksana/FedMix.

Assessment of the Explosion Accident Risk in Non-Coal Mining by Hasse Diagram Technique

The aim of is paper is to address the problem of identifying critical factors in the analysis of non-coal mine explosion accidents as well as to improve the rationality and accuracy of the risk analysis results. Hence, we developed a risk identification method for non-coal mine explosion accidents, combining the Systems-Theoretic Accident Model and Process (STAMP) and the Rank-order Centroid (ROC) method based on the Poset decision-making theory. The proposed method was applied to identify risk in engineering cases. Findings showed that four main dangerous events (out of twelve identified ones) were the primary culprits of related accidents, which were the events “Blasters without licenses and illegal operation” at the basic level, the event of “the confusion about the safety management system of non-coal mine companies” at the control level, and the event of “the failure about the emergency management departments” and “public security departments” at the supervision level. The approximate values of the average rank of the four events are 11.56, 10.4, 4.33, 4.33. The results of risk identification of non-coal mine explosion accidents based on Poset were consistent with the results obtained by the method used in the case study. This study extends the methods for identifying risks of non-coal mine explosion accidents and facilitates the formulation of effective preventive measures.

Clinical effect of standardized nursing for lymphoma patients and the influencing factors of nosocomial infection.

To analyze the clinical effect of standardized nursing for lymphoma patients and the influencing factors of nosocomial infection, a total of 360 diffuse large B-cell lymphoma patients with disease recurrence or progression after first-line treatment were retrospectively selected from our hospital from January 2021 to July 2022. After standardized nursing, the overall infection rate of lymphoma patients was 2.50% (9/360), which was significantly lower than the overall infection rate of our hospital in 2021 (7.44%, 844/11342) (P < .05). The proportion of 3 kinds of pathogenic bacteria detected were G+ bacteria (33.5%), G- bacteria (53.3%), and fungi (13.2%). The pathogenic bacteria genus with the most G+ bacteria is Enterococcus, the pathogenic bacteria genus with the most G+ bacteria is Enterobacteriaceae, and the pathogenic bacteria with the most fungi is Candida albicans. Female infection rate was significantly higher than male (P < .05). There was no significant difference in nosocomial infection among different marital status/fertility status (P > .05). The nosocomial infection of patients with different hospitalization times was statistically significant (P < .05). The duration of hospitalization in the infected group was significantly higher than that in the non-infected group (P < .05). The clinical effect of standardized nursing for lymphoma patients is significant, and the influencing factors of nosocomial infection include patient gender, hospitalization frequency, and hospitalization duration.