syedzayyan/paper_mill_benchmark huggingface dataset:
Prediction Value of Epilepsy Secondary to Inferior Cavity Hemorrhage Based on Scalp EEG Wave Pattern in Deep Learning

To search the predictive value of epilepsy secondary to acute subarachnoid hemorrhage (a sah) based on eeg wave pattern in deep learning.Methods.A total of 156 cases of secondary epilepsy with lower cavity hemorrhage in our hospital were selected and divided into the late epilepsy group and the early epilepsy group according to seizure time, and the nonseizure group and the seizure group according to seizure condition.General data of patients were collected, the eeg types of each group were analyzed, and the disease recurrence rate, treatment effect, and symptom onset time were compared.Results.Rapid and slow and rapid blood flow velocity were the main abnormal manifestations of epilepsy secondary to inferior cavity hemorrhage, accounting for 33.3% and 18.6%, respectively.Compared with the seizure group, the proportion of type ii and type iii in the nonseizure group was higher, and the proportion of type ii and type iii in the early epilepsy group was higher than in the late epilepsy group ( p &lt; 0.05).The diagnostic accuracy, missed diagnosis rate, misdiagnosis rate, specificity, and sensitivity of the eeg wave pattern were 94.9%, 3.2%, 1.9%, 91.7%, and 96.2%, respectively.Compared with the early epilepsy group, the recurrence rate of type iii and type iv in the late epilepsy group was higher ( p &lt; 0.05).The effective rates of the attack group and the nonattack group were 72.7% and 97.0%, respectively.Compared with the attack group, the effective rate of the nonattack group was higher ( p &lt; 0.05).The effective rates of the early epilepsy group and the late epilepsy group were 91.7% and 85.0%, respectively.Compared with the late epilepsy group, the effective rate of the early epilepsy group was higher ( p &lt; 0.05).Compared with the early epilepsy group, the late epilepsy group had longer tonic-clonic seizures, atonic seizures, and absent seizures, and the difference between the groups was statistically significant ( p &lt; 0.05).Conclusion.In a sah secondary epilepsy disease prediction, based on indepth study of the scalp eeg wave type prediction, they play an important role, including a sah high-risk secondary epilepsy wave types for v, iii, and iv types, as well as early and late epilepsy associated with disease stage.Through the diagnosis method to predict the severity of disease, this builds a good foundation for clinical treatment.It is beneficial to improve the effective rate of treatment.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Potential Use of Anti-Cancer Drugs for Treatment of Preeclampsia by Targeting the miRNA-IGF1R-PI3K-AKT Axis

Preeclampsia (pe) belongs to hypertensive disorders of pregnancy (hdp), which can cause maternal death worldwide.This study aimed to identify the mi rna-m rna-associated ce rna network and to find new treatment schedules for pe.Methods.4 microarray datasets were downloaded from the gene expression omnibus database.We obtained 1737 differentially expressed m rnas (865 upregulated and 872 downregulated) and 148 differentially expressed mi rnas (76 upregulated and 72 downregulated) from the placenta tissues of pe, respectively.Functional enrichment analyses of dem rnas were performed.The regulatory relationship between demi rnas and dem rna was predicted via related databases.An mi rna-m rna regulatory network was constructed.Results.Hsa-let-7c and igf1r were identified as potential regulators for pe, and function enrichment analysis showed that the pi3k-akt signaling pathway was closely related.Therefore, ce rnas might regulate the pi3k-akt signaling pathway via the upregulation of igf1r by binding to hsa-let-7c, affecting invasion of trophoblast, angiogenesis, and proinflammation in pe.Further study demonstrated that anticancer drugs including the pi3k inhibitor, akt inhibitor, and igf-1 inhibitor might be a potential solution for pe treatment.Conclusions.The hsa-let-7c/igf1r axis might affect the pi3k-akt signaling pathway which is involved in the pathogenesis of pe, and inhibitors targeting this pathway might be used for pe treatment.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
Analytical Facts of Product Designing, Branding, Packaging, and Distributing through Internet of Things Applications

The unmistakable parts of a decided product can be crucial for imparting the situation of the brand, since these viewpoints are projected as perceived components of the product.Hence, the point of this exploration is to survey the connection between the course of shopper buys right now of securing individual consideration products and the unmistakable parts of packaging as per their generational accomplice.These substantial parts of packaging are the visual perspectives that a product contains, recognized as realistic components and educational components.Deviations in notable improvements stand out.Moreover, deviations in the presence of upgrades influence the manner by which purchasers classify improvements.Our trial examines the impact of the level of deviation of espresso bundles on buyers’ consideration and classification.The boosts are altered bundles of the most popular dutch ground espresso brand.

Journal: Wireless Communications and Mobile Computing (2022)
Publication types: Research Article;
Sports Injury Risk Prevention and MRI Image Performance of Athletes in Physical Education

In order to effectively prevent athletes’ injury during sports training in physical education, a method of risk prevention of sports injury based on mri technology was proposed.This method solves the problem of injury prevention in sports training by studying the association analysis algorithm in data mining technology and the research of mri technology.The experimental results show that the average prediction error of ct and us is about 5%, so it can be considered that the model can predict accurately.Conclusion.The method of risk prevention of sports injury based on mri technology can effectively prevent the injury of athletes in the process of sports training and reduce the injury rate of athletes.

Journal: Scanning (2022)
Publication types: Research Article;
Sports Medical Image Modeling of Injury Prevention in Wushu Training

In order to solve the problem of injury prevention in wushu training, this paper proposes a research on modeling using sports medical images.The main content of this technology research is to drive the muscle strength modeling method based on the sports medical image data.According to the acquisition of mri/ct images, through the research and application of dfis, it is concluded that the research on sports medical image modeling has a high accuracy for injury prevention in wushu training.The experimental results show that translation accuracy ≤ 0.03 ~0.27, rotation accuracy ≤ 0.24 ~0.63, flexion and extension accuracy ≤ 0.1 , translation retest error ≤ 0.2 ~1.2, rotation retest error ≤ 0.5 ~3.4, rotation retest accuracy ≤ 0.4 ~1.04, and sports medical images have a high accuracy for injury prevention in wushu training.It is proved that the research on sports medical image modeling is effective and accurate for the problem of injury prevention in wushu training.

Journal: Scanning (2022)
Publication types: Research Article;
Risk Prediction Method of Obstetric Nursing Based on Data Mining

Obstetric nursing is not only complex but also prone to risks, which can have adverse effects on hospitals.Improper handling of existing risks in obstetric care can lead to enormous harm to patients and families.Therefore, it is necessary to pay attention to the risks of obstetric nursing, especially to predict the risks in a timely manner, and take effective measures to prevent them in time, so as to achieve the purpose of allowing patients to recover as soon as possible.Data mining has powerful forecasting function, so this paper proposes to combine the data‐mining‐based support vector machine method and xgboost method into a forecasting model, which overcomes the shortcomings of unstable forecasting and low accuracy of a single forecasting model.The experimental results of this paper have shown that the prediction accuracy of the svm‐xgboost combined prediction model has reached 100%, the accuracy of the single svm prediction model is about 78%, and the accuracy of the single xgboost prediction model is about 75%.Compared with the single svm model and the xgboost prediction model, the accuracy rate had increased by about 22% and 25%, and the precision rate and recall rate are also improved.Therefore, it is very suitable to use the svm‐xgboost combined prediction model to predict the risk of obstetric nursing.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Research Article;
Revolutionizing E-Commerce Using Blockchain Technology and Implementing Smart Contract

The days of storing data manually are behind us.We are opting for the online form of data storage and transfer.The new era of data digitization comes with its own perks and detriments.Cybersecurity is still a crucial concern today.As more data transfer occurs through an online medium, the risks of a breach and cyberattacks are inevitable.The whole foundation of e-commerce is based on the online transfer of goods and transactions without the need to travel.Transferring transactional data and transactions in e-commerce are prone to cyber threats.Our research’s major objective is to develop a system that protects against such mishaps, especially during the transfer of transactional data, and also implement an automated system that ensures these transactions occur without any errors.To implement this, we are taking advantage of new emerging technologies called blockchain and smart contract.Blockchain allows a decentralized, immutable digital ledger to safely store and transfer data across the network.Blockchain technology is used in e-commerce to transfer transactions in a safe, secure, and faster way.Blockchain enables a peer-to-peer transaction system and data encryption that enables the safe transfer of transactional data.Blockchain is used to transfer transactional data.A smart contract is a special program that enables, verifies, and enforces the terms of a contract digitally.It provides transactional security as the contact is in place.The blockchain, coupled with smart contracts, will revolutionize the future of e-commerce.We have combined blockchain technology to ensure data security and user privacy with smart contracts to ensure that the protocol for the transaction is maintained.The results are presented by building and implementing the proposed system that provides the solution for transactional data privacy.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Research on the Mining of Intangible Cultural Heritage Digital Resources in the Manual Online Teaching System of Preschool Education

Our country’s international status as a cultural power has been further enhanced, and the protection of intangible cultural heritage containing the essence of traditional culture is also gradually being carried out.In addition, with the rapid development of the digital environment, the public’s cultural needs continue to grow, and the contradiction between the supply and demand of public digital cultural services continues to intensify.Converting intangible cultural heritage into digital form for protection and providing resource services for the public has become an important trend in the protection and inheritance of intangible cultural heritage at home and abroad, and it is also an inevitable requirement to solve the contradiction between supply and demand.Improving public cultural services is one of the key projects.At present, our country’s research and practice of intangible cultural heritage digitization and services are also in progress, but there is no research on intangible cultural heritage digital resource services and system construction from the perspective of information service elements.Based on the digital resource service of intangible cultural heritage, the manual course is one of the main skill courses for preschool education majors.At this stage, the short class hours of manual courses, the lack of class hours, the low utilization rate of teaching materials, and the disconnection between the content and the needs of the kindergarten are all problems that need to be solved at present.Just relying on cross-references between schools, the manual knowledge and skills mastered by graduates are not comprehensive enough to complete the manual tasks assigned by the kindergarten.This paper implements the concept of intangible cultural heritage and hopes that by studying the manual knowledge and skills that today’s kindergarten teachers need to possess, the content of existing manual courses can be adjusted in a targeted manner, so that the electronic culture dissemination of manual curriculum resources for preschool education is more reasonable, meeting the requirements of kindergarten teachers in terms of manual knowledge and skills.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Rural Workplace Sustainable Development of Smart Rural Governance Workplace Platform for Efficient Enterprise Performances

In the long developmental process, china’s agriculture has transformed from organic agriculture to inorganic agriculture.New technologies have made the modernization of agriculture possible.However, most older people who are engaged in agriculture may not completely understand the modernization of agriculture.Based on the limitations of traditional image target detection methods, a deep learning‐based pest target detection and recognition method is proposed from a blockchain perspective, to analyze and research agricultural data supervision and governance and explore the effectiveness of deep learning methods in crop pest detection and recognition.The comparative analysis demonstrates that the average precision (ap) of ga‐cpn‐lar (global activation‐characteristic pyramid network‐local activation region) increases by 4.2% compared with other methods.Whether under the inception or res net‐50 backbone networks, the ap of ga‐cpn‐lar is significantly better than other methods.Compared with the res net‐50 backbone network, ga‐cpn‐lar has higher accuracy and recall rates under inception.Precision‐recall curve measurement shows that the proposed method can significantly reduce the false detection rate and missed detection rate.The ga‐cpn‐lar model proposed here has a higher ap value on the mpd dataset than the other target detection methods, which can be increased by 4.2%.Besides, the accuracy and recall of the ga‐cpn‐lar method corresponding to two representative pests under the initial feature extractor are higher than the mpd dataset baseline.In addition, the research results of the mpd dataset and agri pest dataset also show that the pest target detection method based on convolutional neural networks (cnns) has a good presentation effect and can significantly reduce false detection and missed detection.Moreover, the pest regulation based on blockchain and deep learning comprehensively considers global and local feature extraction and pattern recognition, which positively impacts the conscientization of agricultural data processing and promotes the sustainable development of rural areas.

Journal: Journal of Environmental and Public Health (2022)
Publication types: Research Article;
Relationship of Table Tennis Sports Nutritional Food to Sports Athletes’ Training and Physical Health

Table tennis has a broad mass base in our country and is a sport suitable for all ages.It has achieved outstanding results in the international arena and has become our country’s traditional advantage.To engage in professional table tennis, table tennis players are required to have good physical quality.However, table tennis is actually a high-intensity, high-skills sport.It has a very large impact on the main power-generating parts and joints of the athlete’s body.Soldiers and ball players often suffer from sports injuries.Therefore, it is necessary to carry out the nutrition corresponding supplements and targeted training.Therefore, the experimental group members were supplemented with nutritious food to distinguish the control group.The operation steps and experimental principle of this method are provided in detail in this article.Based on the above test scheme, a comparative experiment has been done and a number of physiological tests on the two groups of sports have been carried out.It includes the statistical analysis of athletes’ body composition changes after the experiment and the comparative analysis of body composition before and after nutrition intervention in the experimental group.Analysis of experimental data shows that nutritional food can improve the physical indicators of table tennis players and enhance the overall health evaluation coefficient.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Clinical Study;
Phillygenin Protects the Intestinal Barrier from Dysfunction via let-7b Signaling Pathway and Regulation of Intestinal Microbiota

The study investigates the positive effects of phillygenin on intestinal tight junction via the let-7b signaling pathway and the regulation of intestinal microbiota.The expression levels of tight junction proteins are determined through pcr and western blot.Dss-induced mice colitis is used to verify the protective effects of phillygenin on intestinal barrier and tight junction.Fecal microbiota transplantation is used to verify the role intestinal microbiota.Let-7b is detected in the colon tissues of patients with acute stercoral obstruction.Phillygenin could promote the expression of occludin, which might be inhibited by let-7b inhibitor.Dss-induced mice colitis showed that phillygenin could lower the colonic permeability and maintain the tight junction-associated proteins.The effects of phillygenin could be deprived by anti-let-7b and rescued by fmt of normal intestinal microbiota.Clinical samples verified a lower level of let-7b in stercoral obstruction patients.Phillygenin could protect the intestinal barrier from dysfunction via the signaling pathway of let-7b by regulating intestinal microbiota.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
On Improved 3D-CNN-Based Binary and Multiclass Classification of Alzheimer’s Disease Using Neuroimaging Modalities and Data Augmentation Methods

Alzheimer’s disease (ad) is an irreversible illness of the brain impacting the functional and daily activities of elderly population worldwide.Neuroimaging sensory systems such as magnetic resonance imaging (mri) and positron emission tomography (pet) measure the pathological changes in the brain associated with this disorder especially in its early stages.Deep learning (dl) architectures such as convolutional neural networks (cnns) are successfully used in recognition, classification, segmentation, detection, and other domains for data interpretation.Data augmentation schemes work alongside dl techniques and may impact the final task performance positively or negatively.In this work, we have studied and compared the impact of three data augmentation techniques on the final performances of cnn architectures in the 3d domain for the early diagnosis of ad.We have studied both binary and multiclass classification problems using mri and pet neuroimaging modalities.We have found the performance of random zoomed in/out augmentation to be the best among all the augmentation methods.It is also observed that combining different augmentation methods may result in deteriorating performances on the classification tasks.Furthermore, we have seen that architecture engineering has less impact on the final classification performance in comparison to the data manipulation schemes.We have also observed that deeper architectures may not provide performance advantages in comparison to their shallower counterparts.We have further observed that these augmentation schemes do not alleviate the class imbalance issue.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Numerical Simulation of Particle Deposition in Arterial Bifurcation via Lattice Boltzmann Method

Arterial bifurcation plays a key role in cardiovascular system, so studying the characteristic of the blood flows near bifurcated arteries is of great importance in hemodynamics.The lattice boltzmann (lb) model is used to observe the behavior of the particle deposition near the bifurcated artery.The mechanical quantity, including particle trajectories, velocities, and angular velocities, is studied numerically by lb simulations.The particle is prone to stasis as it is close to the wall of bifurcated vessel for small flow reynolds number.Larger branch angle leads to higher possibility of particle stagnation.The numerical results are consistent with the clinical observation.The study provides a basis for understanding the mechanism of hemodynamics near bifurcations and will provide a research basis for clinical diagnosis and treatment of patients with atherosclerosis.

Journal: Journal of Function Spaces (2022)
Publication types: Research Article;
Nomogram-Based Prediction of Overall and Cancer-Specific Survival in Patients with Primary Bone Diffuse Large B-Cell Lymphoma: A Population-Based Study

Primary bone diffuse large b-cell lymphoma (pd-dlbcl) accounts for more than 80% of primary bone lymphoma.We created two nomograms to predict overall survival (os) and cancer-specific survival (css) in patients with pd-dlbcl for this rare disease.Methods.In total, 891 patients diagnosed with pb-dlbcl between 2007 and 2016 were extracted from the surveillance, epidemiology, and end results (seer) database.Univariate and multivariate cox analyses were performed to explore independent prognostic factors and create nomograms for os and css.The area under the curve (auc), the calibration curve, decision curve analysis (dca), and kaplan–meier (k-m) curve analysis were used to evaluate the nomograms.Results.Four variables were identified as independent prognostic factors for os, and three variables were identified as independent prognostic factors for css.The receiver operating characteristic (roc) curves demonstrated the strong discriminatory power of the nomograms.The calibration and dca curves showed that the nomograms had a satisfactory ability to predict os and css.The k-m curves showed that age, gender, primary site, chemotherapy, and tumor stage affected patient survival.Conclusions.In patients with pd-dlbcl, age, race, primary site, and chemotherapy affected os, while age, race, and chemotherapy affected css.The two nomograms created based on the aforementioned variables provided more accurate individual survival predictions for pd-dlbcl patients and can help physicians make appropriate clinical decisions.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;