syedzayyan/paper_mill_benchmark huggingface dataset:
A Novel Approach to Predict Brain Cancerous Tumor Using Transfer Learning

As the most prevalent and deadly malignancy, brain tumors have a dismal survival rate when they are at their most hazardous.Using mostly traditional medical image processing methods, segmenting and classifying brain malignant tumors is a challenging and time-consuming task.Indeed, medical research reveals that categorization performed manually with the help of a person might result in inaccurate prediction and diagnosis.This is mostly due to the fact that malignancies and normal tissues are so dissimilar and comparable.The brain, lung, liver, breast, and prostate are all studied using imaging modalities such as computed tomography (ct), magnetic resonance imaging (mri), and ultrasound.This research makes significant use of ct and x-ray imaging to identify brain malignant tumors.The purpose of this article is to examine the use of convolutional neural networks (cnns) in image-based diagnosis of brain cancers.It expedites and improves the treatment’s reliability.As a result of the abundance of research on this issue, the provided model focuses on increasing accuracy via the use of a transfer learning method.This experiment was conducted using python and google colab.Deep features were extracted using vgg19 and mobile net v2, two pretrained deep cnn models.The classification accuracy is used to evaluate this work’s performance.This research achieved a 97 percent accuracy rate by mobile net v2 and a 91 percent accuracy rate by the vgg19 algorithm.This allows us to find malignancies before they have a negative effect on our bodies, like paralysis.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
The Effect of Nonpharmacological Integrated Care Protocols on Patients with Fatigue Undergoing Hemodialysis: A Randomized Controlled Trial

This study was designed to investigate the effects of nonpharmacological integrated care protocols on fatigue in patients with hemodialysis.This parallel randomized controlled trial was conducted on patients undergoing hemodialysis from may to october 2020 at the dialysis center of the fifth affiliated hospital of zunyi medical university.The patients were randomized into an intervention group (accepting nonpharmacological integrated care protocols and standard care) or a control group (accepting standard care only) using a computer-generated random number.The nonpharmacological holistic care intervention used in this study involved a well-rounded multidisciplinary team that worked together to improve dietary compliance, medication adherence, and self-management to improve patients’ care and promote self-management.From the 120 evaluated patients, 116 cases were eligible and analyzed.The results showed that patients from the intervention group had obviously reduced overall fatigue, mental fatigue, and muscular fatigue relative to the control group.The nonpharmacological integrated care protocols were interactive and promotive to each other.Meanwhile, the role and function of nurses in the management of chronic disease were demonstrated to be crucial.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Clinical Study;
CY-09 Inhibits NLRP3 Inflammasome Activation to Relieve Pain via TRPA1

Peripheral tissue damage leads to inflammatory pain, and inflammatory cytokine releasing is the key factor for inducing the sensitization of nociceptors.As a calcium ion channel, trpa1 plays an important role in pain and inflammation, thus becoming a new type of anti-inflammatory and analgesic target.However, there is no consensus on the role of this channel in mechanical hyperalgesia caused by inflammation.Here, we aim to explore the role and underlying mechanism of the inflammasome inhibitor cy-09 in two classic inflammatory pain models.We evaluated pain behavior on animal models, cytokine levels, intracellular ca2+ levels, transient trpa1 expression, nf-κb transcription, and nlpr3 inflammasome activation.Consistently, cy-09 reduced the production of inflammatory cytokines, intracellular ca2+ levels, and the activation of trpa1 by inhibiting the activation of inflammasomes, thereby reducing the proinflammatory polarization of macrophages and alleviating animal pain and injury.Importantly, aitc (trpa1 agonist) significantly reversed the analgesic effect of cy-09, indicating that trpa1 was involved in the analgesic effect of cy-09.Our findings indicate that cy-09 relieves inflammation and pain via inhibiting trpa1-mediated activation of nlrp3 inflammasomes.Thus, nlrp3 inflammasome may be a potential therapeutic target for pain treatment and cy-09 may be a pharmacological agent to relieve inflammatory pain, which needs further research.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Study on the Effect of Self-Made Lifei Dingchuan Decoction Combined with Western Medicine on Cough Variant Asthma

S.To observe the clinical efficacy of self-made lifei dingchuan decoction combined with western medicine in the treatment of cough variant asthma (phlegm-heat accumulation in the lung syndrome).Materials and methods.The clinical data of 90 patients with cough variant asthma who were hospitalized in the department of respiratory medicine of our hospital from january 2020 to april 2022 were selected as the research objects, and they were equally divided into the observation group and the reference group according to different treatment methods, 45 cases in each group.The group was treated with traditional montelukast sodium chewable tablet and salmeterol fluticasone mixed powder inhalation, and the observation group was treated with self-made lifei dingchuan decoction on the basis of the control group, saturation, p h, partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide, length of stay, and hospitalization costs.Results.After the patients underwent self-made lifei dingchuan decoction, there were significant differences between the observation group and the reference group in terms of heart rate, respiratory rate, blood oxygen saturation, p h value, arterial blood oxygen partial pressure, carbon dioxide partial pressure, and within the group.There was a statistical difference ( p &lt; 0.05 ).The adverse reactions in patients with cough variant asthma after treatment showed that the red throat, shortness of breath, chest tightness, and dry mouth in the observation group were significantly different from those in the control group ( p &lt; 0.05 ).After investigation, follow-up, and statistics, the hospitalization time, hospitalization cost, asthma exacerbation control time, effective rate, and recurrence rate were compared between the two groups, and the differences between the two groups were statistically significant ( p &lt; 0.05 ).Conclusion.The study on the clinical efficacy and low hospitalization cost of the self-prepared lung and asthma-restorative soup in patients with cough variant asthma significantly improved the patients’ arterial oxygen saturation, acid-base value, arterial partial pressure of oxygen, and partial pressure of carbon dioxide and effectively controlled the heart rate and respiratory rate with high safety, which is worth further promotion.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Clinical Study;Research Article;
Effects and Clinical Value of Peritoneal Dialysis on Water and Water Balance, Adverse Reactions, Quality of Life, and Clinical Prognosis in Patients with Decompensated Chronic Nephropathy: A Systematic Review and Meta-Analysis

To systematically evaluate the effects of peritoneal dialysis and hemodialysis on renal function and quality of life in patients with end-stage renal disease.An evidence-based medical rationale would be provided for peritoneal dialysis or hemodialysis treatment in patients with end-stage renal disease.Methods.The pub med, embase, science direct, cochrane library, china national knowledge infrastructure (cnki), china vip database, wanfang, and china biomedical literature database (cbm) online databases were searched.Comparisons on the effects of peritoneal dialysis on renal function and quality of life were taken between patients with end-stage renal disease (rd).The data were extracted independently by two researchers.The bias-risk-included literatures were assessed according to the cochrane manual 5.1.0 standard.Rev man 5.4 statistical software was used to analyze the collected data via meta-analysis.Results.Seven rct articles were finally included.A total of 745 samples were analyzed via meta-analysis.The obvious heterogeneities of serum creatinine (scr) and blood urea nitrogen (bun) were discovered ( p &lt; 0.00001 ) in the selective investigations.According to the results of this analysis, it was indicated that the renal function of patients with end-stage renal disease treated by peritoneal dialysis was significantly better than that of hemodialysis.According to the meta-analysis, there was obvious heterogeneity of life quality among the included research data.It was indicated that the score of quality of life of patients with end-stage renal disease treated by peritoneal dialysis was significantly better than that of hemodialysis.Conclusion.Compared with hemodialysis in the treatment of end-stage renal disease, the renal function and quality of life of patients with peritoneal dialysis are better than those of hemodialysis.More further studies and follow-up with higher methodological quality and longer intervention time are still needed for further verification.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Meta-Analysis;
What Promotes Medical Overuse: Perspective on Evolutionary Game between Administration and Medical Institutions

Medical overuse is the leading cause of high expenditure among healthcare systems worldwide, with the degree varying from region to region.There is increasing evidence to indicate that in china, national healthcare security administration (nhsa) supervision plays the most crucial role in decreasing medical overuse.For medical overuse, traditional studies focus on empirical researches and qualitative analysis, most of which ignore how the two important participants, i.e., medical institutions and nhsa, affect the strategy of each other.To reduce the losses incurred by insufficient supervision, this study starts from bounded rationality, builds an evolutionary game model to study the relations between the nhsa and medical institutions, and reveals the dynamic evolution process of the supervision of nhsa and overuse of medical institutions.Through stable evolutionary strategy analysis, numerical simulation results, and sensitive experiments under diverse scenarios, we found that when profit gap of medical overuse is high or low, medical institution will adopt fixed strategy, which is medical overuse or appropriate medical use.Only when the profit gap is at a medium level will nhsa’s choice affects medical institutions’ strategy.Furthermore, nhsa’s strategy is affected by the profit gap between medical use and supervision cost.Our work enriches the understanding of supervision for medical overuse and provides theoretical support for the nhsa to make decisions to reach an ideal condition, i.e., to supervise without exertion.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Big Data-Based E-Commerce Transaction Information Collection Method

With the rapid development of e‐commerce industry, online shopping has become a craze.With the rapid growth of transaction volume on e‐commerce platforms, a large amount of transaction data has been accumulated.From the transaction information of these users, a lot of very valuable information can be mined, such as the defects of products and the actual needs of users.In view of the existing e‐commerce transaction information collection method is not mature, in this paper, the electric business platform system architecture planning and design increases the function management module.In this paper, a new naive bayes model is established by using hbase distributed database instead of traditional database.Based on the optimization and extraction of the important transaction information in the product, the dataset of e‐commerce transaction information is updated.Through the efficiency test of the collection method, the information scalability ability test, and the accuracy test, the important context was sorted out after integration, the sources of trading information were sorted out, and the data analysis of the collected information was conducted to optimize the information collection method and verify the feasibility of the method.

Journal: Complexity (2021)
Publication types: Research Article;
A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse.The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated.Big data analysis technology is a new product formed under the background of cloud computing and internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship.On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine (svm) and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis.The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship.The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

Journal: Complexity (2021)
Publication types: Research Article;
Massive Open Online Course Fast Adaptable Computer Engineering Education Model

Massive open online course (mooc) is a new online education model that provides new opportunities and challenges for the development and reform of teaching in colleges and universities.This paper first builds a mooc‐based model of influencing factors of blended learning adaptability.Through investigation and research, it is found that the six influencing factors all have different ways and different degrees of influence on learning adaptability.Among them, learning motivation has a direct and significant impact on learning adaptability, and learning self‐efficacy not only has a direct and significant impact on learning adaptability but also has an indirect impact on learning adaptability through learning motivation.Teacher teaching has indirect effects on learning adaptability through learning self‐efficacy, learning motivation, and learning support.Learning support not only has a direct and significant impact on learning adaptability but also has an indirect impact on learning adaptability through learning motivation.Mooc platform has a direct and significant impact on learning adaptability.The quality of course content has a direct and significant impact on learning adaptability through the mooc platform and learning motivation.The creative results of this research are mainly embodied in the combination of theory and practice, exploring and forming related results based on mooc‐based college students’ learning adaptability.According to the mooc‐based learning‐adaptive intervention model, teaching practice is carried out to verify the effect of the intervention model from two aspects of student procedural performance and result performance.Finally, in view of the problems existing in traditional computer teaching in colleges and universities, combined with the design ideas and basic characteristics of mooc, the teaching mode reform of computer courses is analyzed and discussed, and a mooc‐based computer engineering education teaching mode is proposed.

Journal: Complexity (2021)
Publication types: Research Article;
Prediction of Fish Migration Caused by Ocean Warming Based on SARIMA Model

Herring and mackerel are two of the most important pillars of scottish fisheries.In recent years, global warming has caused a gradual rise in ocean temperatures.In order to survive and reproduce, herring and mackerel populations will migrate.This will have a huge impact on scotland’s fisheries.Therefore, we need to predict the relocation of fish stocks in advance, make timely adjustments to the fishing range, and minimize the loss of the fishing industry.In this article, we subdivide the research target sea area into 39 regions, establish the optimal sarima model for each region based on the collected seawater temperature time series data, and take region 13 and region 15 as examples to fit the arima (3, 3, 1) (1, 2, 1) and arima (2, 3, 1) (0, 2, 1) models with a period of 12.The results show that the sarima model fits well in all regions and predicts the temperature changes in the studied sea area from 2021 to 2050.Finally, according to the predicted sea temperature in different periods, the migration position of the fish school is predicted.

Journal: Complexity (2021)
Publication types: Research Article;
Emergency Project Management Decision Support Algorithm for Network Public Opinion Emergencies Based on Time Series

The present study aims at proposing a time series‐based network public opinion emergency (npoe) management decision support algorithm for the problems of low decision accuracy and long decision time in traditional similar algorithms.In this proposed algorithm, after the time series data are preprocessed, the association rules of the original indicator data of network public opinion emergencies (npoes) are mined, the original indicator data matrix of npoes will be constructed, and the improved local linear embedding approach will be employed to obtain the original indicator data of npoes.After carrying out the preprocessing according to the preprocessing results, the objective weight of the emergency decision index is calculated through the interval value fuzzy information entropy measurement of the emergency decision index, the emergency management decision support model is constructed, and the emergency management decision support of the npoe is realized.The simulation experiment results show that the proposed algorithm has a better effect on the decision‐making effect of the management of npoes, and a higher decision‐making efficiency is achieved.

Journal: Complexity (2022)
Publication types: Research Article;
Analysis of Multiobjective Scheduling Model for Emergency Management under Multiresource Combination of Disaster Chains

This paper analyzes the formation mechanism of urban hazard chains.The results demonstrate that the complex interaction between the disaster‐bearing bodies under the action of disaster‐causing factors is the direct cause of urban hazard chains.The analysis of the energy effects of urban hazard chains shows that the coupling of the excitation energy released by the causative agent and the energy of the disaster‐bearing bodies is the fundamental cause of urban hazard chains.Based on the description of the dynamical mechanism of the urban disaster chain system, this paper first sets up a disaster scenario and considers the effect of the time lag to establish a system dynamics model of the urban disaster chain and urban disaster management.The model of urban disaster management system dynamics shows the mutual influence and complementary relationship between disasters and the economy, pointing out that emphasizing the spill‐over effects of disaster management systems can improve the effectiveness of disaster mitigation.This study also uses equilibrium entropy and brittle entropy theories to characterize the vulnerability of single‐function networks and the degree of brittle association of each lifeline subsystem, respectively, and establishes a model for assessing the sensitivity of lifeline systems to disaster damage.Built on the collection and feedback of information from disaster areas after the occurrence of emergencies, this paper establishes a deterministic multihazard emergency resource dispatches model and an uncertain multihazard emergency resource dispatch model.

Journal: Complexity (2021)
Publication types: Research Article;
The Evolution Model of Public Risk Perception Based on Pandemic Spreading Theory under Perspective of COVID-19

After the occurrence of public health emergencies, due to the uncertainty of the evolution of events and the asymmetry of pandemic information, the public’s risk perception will fluctuate dramatically.Excessive risk perception often causes the public to overreact to emergencies, resulting in irrational behaviors, which have a negative impact on economic development and social order.However, low‐risk perception will reduce individual awareness of prevention and control, which is not conducive to the implementation of government pandemic prevention and control measures.Therefore, it is of great significance to accurately evaluate public risk perception for improving government risk management.This paper took the evolution of public risk perception based on the covid‐19 region as the research object.First, we analyze the characteristics of infectious diseases in the evolution of public risk perception of public health emergencies.Second, we analyze the characteristics of risk perception transmission in social networks.Third, we establish the dynamic model of public risk perception evolution based on seir, and the evolution mechanism of the public risk perception network is revealed through simulation experiments.Finally, we provide policy suggestions for government departments to deal with public health emergencies based on the conclusions of this study.

Journal: Complexity (2021)
Publication types: Research Article;