syedzayyan/paper_mill_benchmark huggingface dataset:
Analysis on Characteristics of Magnetic Resonance Imaging Image under Low-Rank Matrix Denoising Algorithm in the Diagnosis of Cerebral Aneurysm

This study was to explore the effect of a low-rank matrix denoising (lrmd) algorithm based on the gaussian mixture model (gmm) on magnetic resonance imaging (mri) images of patients with cerebral aneurysm and to evaluate the practical value of the lrmd algorithm in the clinical diagnosis of cerebral aneurysm.In this study, the intracranial mri data of 40 patients with cerebral aneurysm were selected to study the denoising effect of the low-rank matrix denoising algorithm based on the gaussian mixture model on mri images of cerebral aneurysm under the influence of rice noise, to evaluate the psnr value, ssim value, and clarity of mri images before and after denoising.The diagnostic accuracy of mri images of cerebral aneurysms before and after denoising was compared.The results showed that after the low-rank matrix denoising algorithm based on the gaussian mixture model, the psnr, ssim, and sharpness values of intracranial mri images of 10 patients were significantly improved ( p &lt; 0.05 ), and the diagnostic accuracy of mri images of cerebral aneurysm increased from 76.2 ± 5.6 % to 93.1 ± 7.9 % , which could diagnose cerebral aneurysm more accurately and quickly.In conclusion, the mri images processed based on the low-rank matrix denoising algorithm under the gaussian mixture model can effectively remove the interference of noise, improve the quality of mri images, optimize the accuracy of mri image diagnosis of patients with cerebral aneurysm, and shorten the average diagnosis time, which is worth promoting in the clinical diagnosis of patients with cerebral aneurysm.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Analysis of the Need for Postoperative Drainage Application for Hip Arthroplasty: A Systematic Review and Meta-Analysis

To synthesize the evidence regarding the effect and safety of drainage after the hip arthroplasty in randomized control trials.Background.Although the standard of hip replacement has matured in recent years, the need for postoperative drainage is still controversial which also is a clinical problem that needs to be addressed.Design.A systematic review and meta-analysis based on the cochrane methods and prisma guideline.Data resources.A systematic search of the cochrane library, pub med, embase, cinahl, ovid, wan fang database, cnki, and cbm database was carried out from january 1, 2000, to december, 2021.Review methods.The quality of included randomized controlled trials was assessed individually by two reviewers independently using criteria recommended in the cochrane handbook for systematic reviews of interventions 5.1.0.Results.Nineteen randomized control trials involving 3354 participants were included in this analysis.From the above analysis, we can know that compared with nondrainage, there was a statistically significant difference in vas score on the postoperative first day ( sd = − 0.6 ; 95% ci: -0.79, -0.41) and second day ( sd = − 0.38 , 95% ci: -0.58, -0.18), hematocrit reduction (md =2.89; 95% ci: 1.3, 4.48), blood transfusion rate (or =1.47; 95% ci: 1.12, 1.92), change of thigh circumstance ( smd = − 0.48 ; 95% ci: -0.66, -0.31), and hospital stay ( md = 1.06 ; 95% ci: 0.73, 1.39) in drainage.However, there were no statistically significant differences in hemoglobin and hematocrit level, hip function, total blood loss, transfusion volume, dressing use, and complications between them.Conclusion.Drainage after hip arthroplasty can reduce swelling in the thigh and relieve pain while no drainage can bring down hematocrit reduction, decrease dressing uses, and shorten the hospital stay which promotes rapid recovery.This review provides a detailed theoretical reference for the proper clinical application of drains and improves the efficient use of resources.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Meta-Analysis;
Analysis of the Effects of Arts and Crafts in Public Mental Health Education Based on Artificial Intelligence Technology

Arts and crafts, with their very different styles due to many factors such as times, regions, technologies, and cultures and nationalities, have undergone an extremely long process, and it is only through continuous superimposition, development, and innovation that they have gradually formed the posture of today’s arts and crafts.Public mental health education is the main way to promote the psychological health development of the public in colleges and universities at present.And among them, sound personality and good self‐awareness is one of the important standards of psychological health of the large public and one of the important tasks of mental health education.As an effective psychological test and treatment method, arts and crafts analysis are an important part of mental health education.It has a certain role in improving the level of self‐awareness and promoting the integration of personality.Art and craft analysis has advantages in mental health and educational group counseling that cannot be replaced by other words and activities, so it can be used in mental health education courses.It can be used in teaching self‐awareness.In order to combine the development of arts and crafts with the development concept and promotion ideas of public mental health education, this article proposes an analysis of the role of arts and crafts in public mental health education based on artificial intelligence computing to enhance the development of arts and crafts from a new perspective and seek the inheritance and innovation of arts and crafts and public mental health education in the new historical period, and proves the proposed method in the relevant dataset.The validity of the proposed method is demonstrated in the relevant dataset.

Journal: Journal of Environmental and Public Health (2022)
Publication types: Research Article;
Analysis of the Effect of Branched Chain Amino Acids on Muscle Health Information of Swimmers Based on Multisensor Fusion and Deep Learning

Swimmers must fully mobilize the muscles of the whole body during exercise, and it is necessary to study the protection of swimmers from muscle damage.Now, muscle damage is increasing year by year, and more athletes are affected.Therefore, studying the causes of muscle injuries and exploring more effective treatments have become important research topics in the field of sports medicine.This study is mainly based on deep learning to analyze the protective effect of branched-chain amino acids on swimming athletes’ muscle injury.Due to the complex and changeable environment and the interference of unknown factors, a single sensor cannot meet the needs of obtaining information.Therefore, people have developed the technology of multisensor information fusion to obtain enough information.Multisensor data fusion technology can synthesize the information of each sensor and then obtain more comprehensive and accurate decision-making information.This study is mainly based on multisensor fusion and deep learning to analyze the impact of branched chain amino acids on swimmers’ muscle health information.Finally, two experiments were designed in this article.The first experimental result showed that the pain level of the experimental group who took bcaa supplements was 19% lower than that of the control group that did not take the bcaa supplement within three days after exercise.The results of the second experiment show the following: after exercise, the creatine kinase activity value of the experimental group taking bcaa supplement was 4.38 ± 1.45 , and the creatine kinase activity value of the control group taking placebo was 5.42 ± 2.12 .It proves that bbca can protect muscle damage by reducing the activity of creatine kinase.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Clinical Study;
Analysis of Risk Factors for Intraoperative Hypotension in Cesarean Section and Poor Prognosis of Neonates

To analyze the risk factors of intraoperative hypotension in cesarean section women and poor prognosis of neonates.Methods.The clinical data of 1071 cesarean section women admitted to the affiliated jiangning hospital of nanjing medical university from january 2021 to december 2021 were retrospectively analyzed.They were divided into hypotension group ( n = 472 ) and normal control group ( n = 599 ) according to whether there was hypotension during operation.The correlations between the clinical data of cesarean section and the occurrence of intraoperative hypotension and poor prognosis of neonates were analyzed by logistic regression analysis.Receiver operating curve (roc) was drawn and the area under the curve (auc) was calculated.Results.Logistic regression analysis results showed that bmi ≥30 kg/m2, infant weight ≥3500 g, spinal anesthesia, puncture site l2-3, bupivacaine dose&gt;10 mg, ropivacaine dose&gt;50 mg, and perfusion index≥4 were the risk factor for intraoperative hypotension in cesarean section ( p &lt; 0.01 ) and bmi ≥30 kg/m2, umbilical cord around neck, spinal anesthesia, and perfusion index≥4 were risk factors for poor prognosis of neonates ( p &lt; 0.01 ).The auc of roc for bmi to diagnose intraoperative hypotension in cesarean section women was 0.6240 (95% ci: 0.59-0.66, p &lt; 0.01 ), the sensitivity was only 30.20% (95% ci: 26.73%-35.02%), and the specificity was 87.65% (84.77%-90.04%), and the auc of bmi for the diagnosis of poor prognosis of neonates was 0.5647 (95% ci: 0.5013-0.6280, p = 0.049 ), and the sensitivity was 51.19% (95% ci: 40.69%-61.59%), and the specificity was 64.34% (61.30%-67.26%).The auc of perfusion index for the diagnosis of intraoperative hypotension in cesarean section women was 0.8333 (95% ci: 0.8081-0.8584, p &lt; 0.01 ), the sensitivity was 94.49% (95% ci: 92.05%-96.21%), and the specificity was 73.12% (69.43%-76.52%); the auc of perfusion index for the diagnosis of roc with poor prognosis of neonates was 0.6164 (95% ci: 0.5538-0.6791, p &lt; 0.01 ), the sensitivity was 70.24% (95% ci: 59.75%-78.96%), and the specificity was 50.86% (47.75%-53.97%).Conclusion.The prediction model established by bmi, infant weight, anesthesia method, puncture site, anesthetic drug dose, and perfusion index has guiding value for clinical prediction of cesarean section maternal hypotension.The prediction model established by bmi, umbilical cord around neck, anesthesia method, and perfusion index has guiding value for clinical prediction of poor prognosis of neonates.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Analysis of Older Adults under Home Care in Taiwan’s Ageing Society

As of january 2022, 16.91% of taiwan’s population was over the age of 65, and a 2017 study indicated that 94.2% of patients who required long-term care in taiwan received home care.This study produced a “post-home care patient information survey” to understand the characteristics of home care patients and the volume and results of home care and investigate the relationships between them.Different diagnoses were found to have no significant effect on the volume or results of home care.Positive correlations were found between the services patients required and the volume of home care and specific results.Volume and specific results were also positively correlated.The termination of home care was primarily due to medical needs (98.6%).As the taiwanese population ages, home care must be improved, and the conditions for which patients can receive home care should be expanded.Care services should replace diagnoses in determining benefit standards for home care payments.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
An Inertial Sensing-Based Approach to Swimming Pose Recognition and Data Analysis

In this paper, inertial sensing is used to identify a swimming stance and analyze its swimming stance data.A wireless monitoring device based on a nine-axis microinertial sensor is designed for the characteristics of swimming motion, and measurement experiments are conducted for different intensities and stances of swimming motion.By comparing and analyzing the motion characteristics of various swimming stances, the basis for performing stroke identification is proposed, and the monitoring data characteristics of the experimental results match with it.The stance reconstruction technology is studied, pc-based open gl multithreaded data synchronization and stance following reconstruction are designed to reconstruct the joint association data of multiple nodes in a constrained set, and the reconstruction results are displayed through graphic image rendering.For the whole system, each key technology is organically integrated to design a wearable wireless sensing network-based pose resolution analysis and reconstruction recognition system.Inertial sensors inevitably suffer from drift after a long period of position trajectory tracking.The proposed fusion algorithm corrects the drift of position estimation using the measurement of the visual sensor, and the measurement of the inertial sensor complements the missing measurement of the visual sensor for the case of occlusion of the visual sensor and fast movement of the upper limb.An experimental platform for upper-limb position estimation based on the fusion of inertial and visual sensors is built to verify the effectiveness of the proposed method.Finally, the full paper is summarized, and an outlook for further research is provided.

Journal: Journal of Sensors (2022)
Publication types: Research Article;
An Architectural Framework for Healthcare Dashboards Design

In today’s competitive environment, one of the new tools in the field of information technology is business or organizational dashboards that are a backup in the process of strategic management of organizations.The purpose of the current research is to provide a framework to design the healthcare dashboard through technical architecture with fulfilling the decision-makers’ requirements.In this study, a common qualitative research method, metasynthesis, is applied, including a seven-step set of research questions, conducting systematic literature search and selection of suitable papers, data extraction, analysis and findings of the qualitative composition, quality control, and presentation of findings.During this process, 102 articles were found by saturation of information resources and then 12 articles were selected for extracting data using acceptance and rejection criteria.A critical evaluation method was used to evaluate the quality of selected articles.After investigating the selected articles and scoring them, in terms of quality, one article was very good, 10 articles were good, and one article was moderate.Then, with regard to the principles and guidelines of technical architecture, the required information was extracted from the selected articles and was analyzed with the method of open, axial, and selective coding.Following the steps of metasynthesis methods, the principles extracted with major and minor titles principles and guidelines in the form of multilayered system architecture including presentation layer, application layer, data layer, and technical infrastructure layer were classified.In the obtained framework, 15 indicators as the main principles and 66 subcriteria as the subsidiary principles for the design and technical architecture of enterprise dashboards were identified.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Review Article;
An Approach to Acquire the Constraints Using Panel Big Data Hybrid Association Rule and Discretization Process for Breast Cancer Prediction

In recent years, big data has become an important branch of computer science.However, without ai, it is difficult to dive into the context of data as a prediction term, relying on a large feature of improving the process of prediction is connected with big data modelling, which appears to be a significant aspect of improving the process of prediction.Accordingly, one of the basic constructions of the big data model is the rule-based method.Rule-based method is used to discover and utilize a set of association rules that collectively represent the relationships identified by the system.This work focused on the use of the apriori algorithm for the investigations of constraints from panel data using the discretization preprocess technique.The statistical outcomes are associated with the improved preprocess that can be applied over the transaction and it can illustrate interesting rules with confidence approximately equal to one.The minimum support provided to the present rule considers constraint as a milestone for the prediction model.The model makes an effective and accurate decision.In nowadays business, several guidelines have been produced.Moreover, the generation method was upgraded because of an association data algorithm that works for dissimilar principles of the structures compared with fewer breaks that are delivered by the discretization technique.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
An Application for Measuring and Analyzing the Level of Performance Accuracy for Health Services Quality Indicators by Using Six-Sigma: A Study Case of Government Hospitals in Khartoum State

The study aimed at acknowledging the six sigma methodology and the existence of the essential components for the application, as well as reducing the time for completing the operations, reducing the error rate to the lowest possible level, and improving the quality of operations.For this objective, the analytical descriptive methodology was used on a sample consisted of 300 administrative and medical staff from khartoum state hospitals (khartoum, omdurman, bahri).To this end, a questionnaire was used for collecting data and for analyzing it and achieving the results of the study by using the statistical analysis package (spss).The study deduced a number of results, the most important of which are that the items of commitment and supreme command support for the senior leadership and the methods of abundant human resources on quality control, and the application of the six sigma methodology in government hospitals in khartoum state achieved a satisfactory level, while continuous improvement paragraphs, processes, and systems on quality control and the application of six sigma methodology achieved high quality.There is a significant effect on the extent of commitment and support of the higher leadership on quality control and the application of the six sigma methodology.Similarly, there is a statistically significant effect on the application of continuous improvement methods on quality control and six sigma methodology.Also, there is a statistically significant effect on the application of the abundance of human resources methods variable on quality control and the application of six sigma methodology in governmental hospitals in khartoum state.The study recommended to take interest in the six sigma methodology and assure the possibility of using it in khartoum state’s hospitals because of its scientific and practical importance in improving the quality of services and provided processes, and the need to provide qualified financial and human resources for using and developing six sigma methodology in hospitals, as well as great attention in training and providing departments heads with full knowledge of six sigma methodology and the fundamentals on which six sigma methodology, is based on its importance for hospitals.The study also recommended associating the promotions system in government hospitals in khartoum state with the quality control program.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Advanced Computing Approach for Modeling and Prediction COVID-19 Pandemic

The emergence of many strains of the coronavirus, including the latest omicron strain, which is spreading at a very high speed, is leading to the world health organization’s (who) concern about the creation of this new mutation.Therefore, there is a strong motivation for modeling and predicting covid-19 to control the number of cases of the disease.The proposed system for predicting the number of cases of covid-19 can help governments take precautions to prevent the spread of the disease.In this paper, a statistical logistic growth model was employed to predict the spread of covid-19 in australia and brazil.The datasets were collected from the surveillance systems in australia and brazil from march 13, 2020, to december 12, 2021, for 641 days.This proposed method used a tested logistic growth model for the complex spread of covid-19 and forecasted future values within a time interval of six days.The results of the predicted, cumulative, confirmed cases indicate the robustness and effectiveness of the proposed system, which was categorized by time-dependent dynamics.The coefficient of determination ( r ) metric was used to evaluate the model to predict covid-19, and the proposed system scored the highest correlation ( r 2 = 99 % ).The proposed system has the potential to contribute to public health by making decisions about how to prevent the spread of covid-19.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Activation of Neural Modeling-Related Genes in the Heart of Mice after Gamma Irradiation

Radiation-induced heart disease (rihd) is a common sequela of thoracic irradiation.At the same time, nerve remodeling is involved in the progression of heart disease.However, the activation of the nerve remodeling related genes in radiation-induced heart disease is still lacking.Methods.In this study, c57bl/j mice was anesthetized by intraperitoneal injection with pentobarbital sodium (2%, 40 mg/kg), and radiation was delivered using a cobalt-60 (60co) teletherapy unit (cirus).When the mice were anesthetized, none of them showed the signs of peritonitis, pain, or discomfort.The mice hearts were exposed to a γ-radiation field of 5 mm × 5 mm .The total dose of γ-radiation was 3 gy/day for each animal for 5 consecutive days.The mice were executed by severed neck, and its limbs were weak.Quantitative polymerase chain reaction (q pcr) and immunohistochemistry were used to explore the possible mechanism of arrhythmia in patients with rihd.Results.Our results demonstrated that growth-associated protein 43 (gap43) was increased significantly after radioactive heart injury compared with the control group.Moreover, the protein expression of tyrosine hydroxylase (th) and choline acetyl-transferase (chat) was significantly decreased compared with the control group and gradually increased with time rend.The nerve growth factor (ngf) was remarkably increased after radiation-induced heart injury compared with the control group.Immunohistochemistry results indicated that the nerve growth factors gap43 and ngf were significantly increased after radiation-induced heart injury.Conclusions.Chest radiotherapy could activate the neural modeling related genes in rihd.This may provide a new treatment plan for the future treatment of heart problems caused by chest radiotherapy.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;