syedzayyan/paper_mill_benchmark huggingface dataset:
Investigation on the Relationship between Sleep Quality and Depression and Anxiety in Hospitalized Patients with Different Levels of AECOPD

To explore the correlations between sleep quality and depression and anxiety in hospitalized patients with acute exacerbation of chronic obstructive pulmonary disease (aecopd).Methods.A total of 131 aecopd patients treated at no.6th people’s hospital affiliated to shanghai jiao tong university school from january 2018 to december 2020 were selected and divided into the classes i ( n = 30 ), ii ( n = 23 ), iii ( n = 37 ), and iv ( n = 41 ) based on the severity of aecopd.The pittsburgh sleep quality index (psqi) and the hospital anxiety and depression scale (hads) were employed to assess the quality of sleep and anxiety/depression in aecopd patients.The pearson correlation analysis explored the associations between psqi score and hads anxiety/depression score.Binary logistic regression was utilized to determine risk factors for anxiety/depression in aecopd patients.Results.The psqi score, hads anxiety score, and hads depression score in patients with aecopd class iii and class iv were significantly higher than those of classes i and ii.The severe anxiety and depression ratio were significantly different among patients with classes i–iv aecopd.The severity of aecopd was significantly correlated with the psqi score ( r = 0.51 , p &lt; 0.001 ), hads anxiety score ( r = 0.66 , p &lt; 0.001 ), and hads anxiety score ( r = 0.65 , p &lt; 0.001 ).Binary logistic regression analysis showed that the copd duration, the severity of aecopd, and psqi score were the risk factors for anxiety and depression in patients with aecopd.Conclusions.Poor sleep quality, anxiety, and depression are common in patients with aecopd.Improvement of sleep quality may help to alleviate anxiety and depression in aecopd patients.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Intracavitary Electrocardiogram Guidance Aids Excavation of Rhythm Abnormalities in Patients with Occult Heart Disease

In this paper, the analysis of intracavitary electrocardiograms is used to guide the mining of abnormal cardiac rhythms in patients with hidden heart disease, and the algorithm is improved to address the data imbalance problem existing in the abnormal electrocardiogram signals, and a weight-based automatic classification algorithm for deep convolutional neural network electrocardiogram signals is proposed.By preprocessing the electrocardiogram data from the mit-bih arrhythmia database, the experimental dataset training algorithm model is obtained, and the algorithm model is migrated into the project.In terms of system design and implementation, by comparing the advantages and disadvantages of the electrocardiogram monitoring system platform, the overall design of the system was carried out in terms of functional and performance requirements according to the system realization goal, and a mobile platform system capable of classifying common abnormal electrocardiogram signals was developed.The system is capable of long-term monitoring and can invoke the automatic classification algorithm model of electrocardiogram signals for analysis.In this paper, the functional logic test and performance test were conducted on the main functional modules of the system.The test results show that the system can run stably and monitor electrocardiogram signals for a long time and can correctly call the deep convolutional neural network-based automatic electrocardiogram signal classification algorithm to analyze the electrocardiogram signals and achieve the requirements of displaying the electrocardiogram signal waveform, analyzing the heartbeat type, and calculating the average heart rate, which achieves the goal of real-time continuous monitoring and analysis of the electrocardiogram signals.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Intra- and Interrater Agreement of Face Esthetic Analysis in 3D Face Images

The use of three‐dimensional (3d) facial scans for facial analysis is increasing in maxillofacial treatment.The aim of this study was to investigate the consistency of two‐dimensional (2d) and 3d facial analyses performed by multiple raters.Six men and four women (25–36‐year‐old) participated in this study.The 2d images of the smiling and resting faces in the frontal and sagittal planes were obtained.The 3d facial and intraoral scans were merged to generate virtual 3d faces.Ten clinicians performed facial analyses by investigating 14 indices of 2d and 3d faces.Intra‐ and interrater agreements of the results of 2d and 3d facial analyses within and among the participants were evaluated.The intrarater agreement between the 2d and 3d facial analyses varied according to the indices.The highest and lowest agreements were found for the dental crowding index (0.94) and smile line curvature index (0.56) in the frontal plane, and angle’s classification (canine) index (0.98) and occlusal plane angle index (0.55) in the profile plane.In the frontal plane, the interrater agreements were generally higher for the 3d images than for the 2d images, while in the profile plane, the interrater agreements were high in the angle’s classification (canine) index however low in the other indices.Several occlusion‐related indices were missing in the 2d images because the posterior teeth were not observed.Esthetic analysis results between 2d and 3d face images can differ according to the evaluation indices.The use of 3d faces is recommended over 2d images to increase the reliability of facial analyses, as it can fully assess both esthetic and occlusion‐related indices.

Journal: BioMed Research International (2023)
Publication types: Research Article;
Interventional Treatment of Bronchiectasis Macrosomia Based on Multirow CT Tomography Monitoring

We present in this paper an in-depth study and analysis of bronchiectasis haemoptysis by multirow ct tomography and a multifaceted treatment and analysis of the interventions monitored by the scan.Although coronary ct is of great clinical value in the diagnosis and monitoring of coronary artery disease, the potential radiation damage caused by coronary ct should not be underestimated because ct imaging is based on x-rays and the actual effective dose is 5–30 m sv, which is reported in the literature to be high when using conventional imaging modalities for coronary ct.Although there is no direct evidence of a definite causal relationship between x-ray exposure during ct examinations and tumorigenesis, theoretically, even small doses of radiation exposure may pose some potential health risk.Therefore, in clinical practice, coronary ct examinations should be performed in strict compliance with the radiation protection rule “as low as reasonably achievable” (alara) recognized by the radiation industry.For longitudinal openings in the range of 0° to 59° and transverse openings in the range of 0° to 44°, the cb2 catheter is significantly more stable than the mik catheter, and for longitudinal openings in the range of 60° to 119° and transverse openings in the range of 0° to 44°, the cb2 catheter is more stable than the mik catheter.For longitudinal openings from 0° to 120° and lateral openings from 45° to 90°, there was no significant difference in cannulation stability between the cb2 and mik catheters.There was a potential tendency for mik cannulation stability to be higher than cb2 for longitudinal openings in the range of 120° to 180° and lateral openings in the range of 45° to 90°, but there was no significant difference.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Interpretable Diagnosis for Whole-Slide Melanoma Histology Images Using Convolutional Neural Network

At present, deep learning-based medical image diagnosis had achieved high performance in several diseases.However, the black-box nature of the convolutional neural network (cnn) limits their role in diagnosis.In this study, a novel interpretable diagnosis pipeline using the cnn model was proposed.Furthermore, a sizeable melanoma database that contains 841 digital whole-slide images (wsis) was built to train and evaluate the model.The model achieved strong melanoma classification ability (0.962 areas under the receiver operating characteristic, 0.887 sensitivity, and 0.925 specificity).Moreover, the proposed model outperformed the existing schemes in terms of accuracy that is 20 pathologists (0.933 vs 0.732 accuracy).Finally, the gradient-weighted class activation mapping (grad-cam) method was used to show the inner logic of the proposed model and its feasibility to improve diagnosis process in healthcare.The mechanism of feature heat maps which is visualized through a saliency mapping has demonstrated that features learned or extracted by the proposed model are compatible with the accepted pathological features.Conclusively, the proposed model provides a rapid and accurate diagnosis by locating the distinctive features of melanoma to build doctors’ trust in the cnns’ diagnosis results.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Interoperability Requirements for Blockchain-Enabled Electronic Health Records in Healthcare: A Systematic Review and Open Research Challenges

A distributed ledger system blockchain proves to be worthy in the domain of healthcare due to its enormous applications and benefits.Peer-to-peer devolved transactions in an allocated way make the blockchain an efficient and modern tool to be utilized in healthcare as a solution to problems and challenges.The traditional healthcare system utilizes classical approaches to manage and maintain the ehr and cross-domain implementation.Therefore, a systematic investigation is necessary to find the current research trends, challenges, and solutions to implement blockchain to address the challenges.The motivation of this study is to pave the way for future research to find more problem-specific solutions by implementing blockchain to make the healthcare system more robust.The presented systematic survey provides the visualization and graphical representation of current methodologies, challenges, and future directions.The bibliometric analysis has been performed on the published studies in scopus from 2017 to 2021.The publication published in the first three months of 2021 in the domain of healthcare using blockchain has also been reviewed to find the latest trends in the blockchain.The study covers multiple challenges in the presented systematic literature review, especially the interoperability of blockchain-based systems in the healthcare domain.The presented study results show the top trending research topics, top-ranked authors, and top institutes focusing on blockchain around the world.The proposed study provides a baseline for future challenges and solutions related to blockchain implementation in healthcare.

Journal: Security and Communication Networks (2022)
Publication types: Review Article;
Interbank Offered Interest Rate Risk Measurement Based on Embedded Sensor Network

Interbank lending rate is the main benchmark interest rate in the domestic currency market, looking for an appropriate financial time series model to describe its stochastic fluctuation process, and choosing an appropriate risk measurement method to measure the domestic interbank lending interest rate risk.The risk management of the interest rate market has great theoretical and practical significance.This article is aimed at studying the interbank interest rate risk measurement based on the embedded sensor network and proposes the key technology of sensor network, sensor network mac layer protocol, leach energy model, and other methods in the article.Related experiments have been carried out on the interbank interest rate risk measurement.The experimental results show that the interbank interest rate risk measurement model based on the embedded sensor network is much more efficient than the traditional interest rate risk measurement model.This has reduced the bank’s loss of interest rate by at least 7%.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
Intelligent Algorithm-Based Multislice Spiral Computed Tomography to Diagnose Coronary Heart Disease

In this study, dictionary learning and expectation maximization reconstruction (dlem) was combined to denoise 64-slice spiral ct images, and results of coronary angiography (cag) were used as standard to evaluate its clinical value in diagnosing coronary artery diseases.120 patients with coronary heart disease (chd) confirmed by cag examination were retrospectively selected as the research subjects.According to the random number table method, the patients were divided into two groups: the control group was diagnosed by conventional 64-slice spiral ct images, and the observation group was diagnosed by 64-slice spiral ct images based on the dlem algorithm, with 60 cases in both groups.With cag examination results as the standard, the diagnostic effects of the two ct examination methods were compared.The results showed that when the number of iterations of maximum likelihood expectation maximization (mlem) algorithm reached 50, the root mean square error (rmse) and peak signal to noise ratio (psnr) values were similar to the results obtained by the dlem algorithm under a number of iterations of 10 when the rmse and psnr values were 18.9121 d b and 74.9911 d b, respectively.In the observation group, 28.33% (17/60) images were of grade 4 or above before processing; after processing, it was 70% (42/60), significantly higher than the proportion of high image quality before processing.The overall diagnostic consistency, sensitivity, specificity, and accuracy (88.33%, 86.67%, 80%, and 85%) of the observation group were better than those in the control group (60.46%, 62.5%, 58.33%, and 61.66%).In conclusion, the dlem algorithm has good denoising effect on 64-slice spiral ct images, which significantly improves the accuracy in the diagnosis of coronary artery stenosis and has good clinical diagnostic value and is worth promoting.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Integrated Microarray Analysis to Identify Genes and Small-Molecule Drugs Associated with Stroke Progression

Several blood biomarkers are now considered increasingly important for stratifying risk, monitoring disease progression, and evaluating the response to therapy in ischemic stroke.The purpose of the present study was to identify the key genes associated with ischemic stroke progression and elucidate the potential therapeutic small molecules.Microarray datasets related to stroke for gse58294, gse22255, and gse16561 were obtained from the gene expression omnibus (geo) database.Differentially expressed genes (degs) were filtered using the limma package.David was then searched to perform gene ontology (go) and pathway enrichment analyses.Based on the degs, a protein-protein interaction (ppi) network was developed using cytoscape, and mcode was applied to conduct module analysis.Finally, to identify the potential drugs for ischemic stroke, the connectivity map (cmap) database was used.Sixty degs were identified after analyzing the three datasets.The go data analysis revealed that the degs were significantly associated with biological processes, including positive regulation of programmed cell death, protein localization in organelles, and positive regulation of apoptosis.Kegg analysis showed that the degs were particularly enriched in the fc epsilon ri signaling pathway, mapk signaling pathway, and huntington’s disease.We selected five degs with high connectivity (cybb, syk, dusp1, tnf, and sp1) that significantly predicted stroke progression.In addition, cmap prediction showed ten small molecules that could be used as adjuvants when treating ischemic stroke.The outcomes of the present study indicated that the five genes mentioned above can be considered potential targets for developing new medications that can modify the ischemic stroke process, and mycophenolic acid was the most promising small molecule to treat ischemic stroke.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
Integrated Bioinformatics Analysis for Identification of the Hub Genes Linked with Prognosis of Ovarian Cancer Patients

One of the most usual gynecological state of tumor is ovarian cancer and is a major reason of gynecological tumor-related global mortality rate.There have been multiple risk elements related to ovarian cancer like the background of past cases associated with breast cancer or ovarian cancer, or excessive body weight issues, case history of smoking, and untimely menstruation or menopause.Because of unclear expressions, more than 70% of the ovarian cancer patient cases are determined during the early stage.Material and methods.Gse38666, gse40595, and gse66957 were the three microarray datasets which were analyzed using geo2r for screening the differentially expressed genes.Go, kyoto encyclopedia of genes, and protein expression studies were performed for analysis of hub genes.Then, survival analysis was performed for all the hub genes.Results.From the dataset, a total of 199 differentially expressed genes (degs) were identified.Through the kegg pathway study, it was noted that the degs are mainly linked with the age-rage signaling pathway, central carbon metabolism, and human papillomavirus infection.The survival analysis showed 4 highly expressed hub genes col4a1, sdc1, cdkn2a, and top2a which correlated with overall survival in ovarian cancer patients.Moreover, the expression of the 4 hub genes was validated by the gepia database and the human protein atlas.Conclusion.The results have shown that all 4 hub genes were found to be upregulated in ovarian cancer tissues which predict poor prognosis in patients with ovarian cancer.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Insulin Topical Application for Wound Healing in Nondiabetic Patients

Low-cost and safe strategies to improve wound healing will be of great social and economic value.The goal of this pilot clinical trial is aimed at analyzing how effective insulin therapy is at healing wounds in nondiabetic people.Methods.In this protocol research, 346 individuals were included.Patients were divided as 2 groups at random: experimental patients were given a ten-unit answer.For each 10 cm2 of wound, insulin was injected in solution with 1 m l 0.9 percent saline, whereas the control group got a standard dressing with normal saline.Results.During the therapy period, no adverse effects were reported.After insulin therapy, no substantial insulin-related side effects were reduced.After 10 days of therapy, the experimental group’s granulation tissue coverage rate and thickness were considerably improved as compared to control.Furthermore, a momentous difference in the occurrence of wound bleeding and suppurative wounds between the two groups ( p = 0.05 ).Conclusion.The results of this pilot research suggest that insulin injections could harmless and effective alternative therapy for wound healing in nondiabetic individuals and that larger, placebo-controlled trials are needed to evaluate effectiveness and safety of insulin treatment in wound healing patients.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Clinical Study;
NLRC4 Gene Single Nucleotide Polymorphisms Are Associated with the Prognosis of Hemophagocytic Lymphohistiocytosis

To analyze and study the correlation between nlr family card domain-containing 4 (nlrc4) gene single nucleotide polymorphisms and the prognosis of patients with hemophagocytic lymphohistiocytosis (hlh).Methods.In this study, we retrospectively studied the clinical data of 62 hlh patients, including 40 males and 22 females.The genomic dna was extracted, and the genotypes at rs385076 locus and rs479333 locus of the nlrc4 gene were analyzed.The level of blood interleukin-18 (il-18) was analyzed by enzyme-linked immunosorbent assay (elisa).Results.Compared with the tt genotype at the nlrc4 gene rs385076 locus, the mortality of hlh patients with tc genotype and cc genotype was higher ( rr = 3.205 , 95% ci: 1.277-4.788, p = 0.012 ; rr = 3.052 , 95% ci: 1.098-4.753, p = 0.031 ).Taking the cc genotype at rs479333 of the nlrc4 gene as a reference, hlh patients with cg genotype and gg genotype had a higher risk of death ( rr = 3.475 , 95% ci: 1.488-5.775, p = 0.003 ; rr = 2.986 , 95% ci: 1.014-5.570, p = 0.047 ).Nlrc4 gene rs385076 t&gt;c and rs479333 c&gt;g were significantly related to the poor prognosis of hlh patients.The area under the curve (auc) of the receiver operating curve (roc) for the prognostic outcome of hlh with serum il-18 level was 0.6813 (95% ci: 0.5365-0.8260, p = 0.0189 ).Nlrc4 gene rs385076 t&gt;c and rs479333 c&gt;g were related to higher serum il-18 levels.Conclusion.Nlrc4 gene rs385076 t&gt;c and rs479333 c&gt;g are related to the poor prognosis of hlh patients.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Influences of Antithrombotic Elastic Socks Combined with Air Pressure in Reducing Lower Extremity Deep Venous Thrombosis for Patients Undergoing Cardiothoracic Surgery

This study was designed to investigate the application and therapeutic effect of antithrombotic elastic socks combined with air pressure in the prevention of lower extremity deep venous thrombosis in patients undergoing cardiothoracic surgery.Sixty patients in cardiothoracic surgery of our hospital from january 2019 to december 2020 were randomly divided into a study group and control group.The control group was treated with routine treatment intervention.Based on routine treatment intervention, the study group was treated with antithrombotic elastic socks combined with pneumatic treatment intervention.The activated partial thromboplastin time (aptt), thrombin time (tt), femoral venous blood flow velocity of both lower limbs, and the incidence of lower extremity deep venous thrombosis (ledvt), postoperative lower extremity swelling, inflammatory factors, and satisfaction were measured.After intervention, aptt ( 31.74 ± 1.15 s) and tt ( 14.58 ± 0.24 s) in the study group were higher than those in the control group aptt ( 25.13 ± 1.14 s) and tt ( 12.14 ± 0.23 s) ( p &lt; 0.05 ).The left lower limb femoral vein blood flow velocity and the right lower limb femoral vein blood flow velocity in the study group were better than those in the control group ( p &lt; 0.05 ).The incidence of postoperative lower limb swelling and deep vein in the study group was lower than that in the control group ( p &lt; 0.05 ).Serum tumor necrosis factor alpha and interleukin-6 concentrations in the study group were lower than those in the control group ( p &lt; 0.05 ).The satisfaction rate of patients in the study group (93.33%) was significantly higher than that in the control group (70.00%) ( p &lt; 0.05 ).In conclusion, after cardiothoracic surgery, antithrombotic elastic socks combined with air pressure can significantly reduce the incidence of ledvt by improving patients’ coagulation function, reducing inflammatory reaction.It is worthy of popularization and application in relevant surgery.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Clinical Study;