syedzayyan/paper_mill_benchmark huggingface dataset:
Deep Learning-Based Detection and Diagnosis of Subarachnoid Hemorrhage

Subarachnoid hemorrhage (sah) is one of the critical and severe neurological diseases with high morbidity and mortality.Head computed tomography (ct) is among the preferred methods for the diagnosis of sah, which is confirmed by ct showing high-density shadow in the subarachnoid space.Analysis of these images through a deep learning-based subarachnoid hemorrhage will reduce the approximate rate of misdiagnosis in general and missed diagnosis by clinicians in particular.Deep learning-based detection of subarachnoid hemorrhage mainly includes two tasks, i.e., subarachnoid hemorrhage classification and subarachnoid hemorrhage region segmentation.However, it is difficult to effectively judge reliability of the model and classify bleeding which is based on limited predictive probability of convolutional neural network output.Moreover, deep learning-based bleeding area segmentation requires a large amount of training data to be marked in advance and the large number of network parameters makes the model training unable to reach the optimal.To resolve these problems associated with existing models, bayesian deep learning and neural network-based hybrid model is presented in this paper to estimate uncertainty and efficiently classify subarachnoid hemorrhage.Uncertainty estimation of the proposed model helps in judging whether the model’s prediction is reliable or not.Additionally, it is used to guide clinicians to find the neglected subarachnoid hemorrhage area.In addition, a teacher-student mechanism deep learning model was designed to introduce observational uncertainty estimation for semisupervised learning of subarachnoid hemorrhage.Observation uncertainty estimation detects the uncertain bleeding areas in ct images and then selects areas with high reliability.Finally, it uses these unlabeled data for model training purposes as well.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Deep Learning Enabled Diagnosis of Children’s ADHD Based on the Big Data of Video Screen Long-Range EEG

Attention-deficit hyperactivity disorder (adhd) is a common neurodevelopmental disorder in children.At the same time, adhd is prone to coexist with other mental disorders, so the diagnosis of adhd in children is very important.Electroencephalogram (eeg) is the sum of the electrical activity of local neurons recorded from the extracranial scalp or intracranial.At present, there are two main methods of long-range eeg monitoring commonly used in clinical practice: one is ambulatory eeg monitoring, and the other is long-range video eeg monitoring.The purpose of this study is to summarize the brain electrical activity and clinical characteristics of children with adhd through the video long-range computer graphics data of children with adhd and to explore the clinical significance of video long-range eeg in the diagnosis of children with adhd.For a more effective analysis, this study further processed the video data of long-range computer graphics of children with adhd and constructed several neural network algorithm models based on deep learning, mainly including fully connected neural network models and two-dimensional convolutional neural networks.Model and long- and short-term memory neural network model.By comparing the recognition effects of these several algorithms, find the appropriate recognition algorithm to improve the accuracy and then establish a recognition method for the diagnosis of children’s adhd based on deep learning long-range eeg big data.Finally, it is concluded that long-term video eeg can analyze the eeg relationship of children with adhd and provide a diagnostic basis for the diagnosis of adhd.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
Decoding the Mechanism behind the Pathogenesis of the Focal Segmental Glomerulosclerosis

Focal segmental glomerulosclerosis (fsgs) is a chronic glomerular disease associated with podocyte injury which is named after the pathologic features of the kidney.The aim of this study is to decode the key changes in gene expression and regulatory network involved in the formation of fsgs.Integrated network analysis included gene expression omnibus (geo) datasets to identify differentially expressed genes (degs) between fsgs patients and healthy donors.Bioinformatics analysis was used to identify the roles of the degs and included the development of protein-protein interaction (ppi) networks, gene ontology (go), and the kyoto encyclopedia of genes and genomes (kegg) pathway enrichment analyses, and the key modules were assured.The expression levels of degs were validated using the additional dataset.Eventually, transcription factors and ce rna networks were established to illuminate the regulatory relationships in the formation of fsgs.1130 degs including 475 upregulated genes and 655 downregulated genes with functional enrichment analysis were determined.Further analysis uncovered that the validated hub genes were defined as candidate genes, including complement c3a receptor 1 (c3ar1), c-c motif chemokine receptor 1(ccr1), c-x3-c motif chemokine ligand 1 (cx3cl1), melatonin receptor 1a (mtnr1a), and purinergic receptor p2y13 (p2ry13).More importantly, we identified transcription factors and m rna-mi rna-lnc rna regulatory networks associated with the candidate genes.The candidate genes and regulatory networks discovered in this study can help to comprehend the molecular mechanism of fsgs and supply potential targets for the diagnosis and therapy of fsgs.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Data Mining-Based Clinical Study on the Effect of Oral Restoration Film in Guiding Oral Bone Regeneration and Dental Implantation

Oral repair membrane guided oral bone regeneration, particularly in dental implants, is a guided regeneration technology for bone tissue.The principle is based on the characteristics of rapid migration of epithelial cells and fibroblasts and slower migration of osteoblasts.Materials are placed in the bone defect, creating a relatively closed environment which is conducive to the growth of bone tissue.In this paper, we have evaluated clinical effects of hai’ao oral repair membrane as a barrier membrane to guide bone regeneration in implants.For this purpose, certain treatment data are collected through data mining and patient’s names with bone defects in the implantation area are selected.According to the randomness principles, these patients are divided into experimental and control groups and preoperative examinations along with basic periodontal treatments are performed on the selected cases.Furthermore, we have analyzed different effects by comparing treatment conditions.Experimental results, as a technical shielding film, verify that hai’ao oral repair membrane meets requirements of safety and no immune rejection.It plays a role in promoting bone formation around the implant.Mid-to-long-term follow-up is satisfactory with no related complications.At the same time, it has the advantages of simple operation, reduced patient suffering, convenient transportation and storage, and longer validity period.Compared with the control group in terms of safety evaluation of postoperative vital signs, laboratory examinations, and incision healing, hai’ao oral repair membrane has no significant difference.Postoperative osteogenesis effect is equivalent to that of the control group and meets requirements of superiority.Hai’ao oral repair membrane is used as a shielding membrane material in implant surgery technology to guide bone regeneration.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Dapagliflozin Ameliorates STZ-Induced Cardiac Hypertrophy in Type 2 Diabetic Rats by Inhibiting the Calpain-1 Expression and Nuclear Transfer of NF-κB

To investigate the effect of dapagliflozin (dapa) on cardiac hypertrophy induced by type 2 diabetes mellitus (t2dm) and its mechanism.Methods.Sd rats with t2dm were divided into a t2dm group ( n = 6 ) and dapa group ( n = 6 ).They were, respectively, fed with the same amount of normal saline and 1 mg/kg dapa.The control group ( n = 6 ) was also fed with normal saline.The hearts were tested by the application of echocardiography and hemodynamics.Subsequently, fasting blood glucose (fbg), serum total cholesterol (tc), and triglyceride (tg) as well as interleukin- (il-) 10, il-6, and tumor necrosis factor (tnf)-α in serum were tested.H&amp;e and masson staining was performed to observe the degree of cardiac tissue lesions, and expression of atrial natriuretic peptide (anp), brain natriuretic peptide (bnp), calpain-1, p-iκbα, and p65 in myocardial tissue was tested by q rt-pcr and western blot.Results.Compared with the control group, rats in the t2dm group exhibited significant diabetic symptoms: fbg was significantly elevated, and the levels of tc, tg, il-6, and tnf-α were significantly increased, while the levels of il-10 and the calpain activity were evidently decreased.However, dapa treatment could improve the above changes.At the same time, the damage and fibrosis of the heart tissue in the dapa group were markedly improved.Additionally, the m rna expression of anp and bnp in myocardial tissue of the dapa group was markedly increased.And dapa could inhibit the expression of p-iκbα/iκbα in the cytoplasm and p65 in the nucleus as well as the expression of calpain-1 in myocardial tissue.Conclusion.Dapa treatment ameliorates the cardiac hypertrophy caused by t2dm by decreasing body blood glucose, while reducing the expression of calpain-1 in cardiomyocytes and inhibiting the nuclear translocation of nf-κb.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Correlation between the Expression of VEGF and Ki67 and Lymph Node Metastasis in Non-small-Cell Lung Cancer: A Systematic Review and Meta-Analysis

Lymph node metastasis is the most common and important way of metastasis in nsclc and is also the most important factor affecting lung cancer stage and prognosis.It is very important to analyze the relationship between the expression of vascular endothelial growth factor (vegf) and ki67 and lymph node metastasis (lnm) in non-small-cell lung cancer (nsclc).Methods.We searched the pub med, embase, and cochrane library and conducted meta-analyses using the r meta-package.Relative risk (rr) with a 95% confidence interval (95% ci) was the main indicator.Results.Totally, 18 studies were considered eligible, with 4521 patients, including 1518 lnm-positive patients and 3033 lnm-negative patients.The incidence of lnm in ki67-negative patients was lower than that in ki67-positive patients (rr = 0.66, 95% ci: 0.44, 0.98).The incidence of lnm in vegf-a-negative patients was lower than that in vegf-a-positive patients (rr = 0.64, 95% ci: 0.49, 0.83).The incidence of lnm in vegf-c negative patients was lower than that in vegf-c positive patients (rr = 0.68, 95% ci: 0.53, 0.88).The incidence of lnm in vegf-d negative and positive patients were of no significant differences (rr = 0.84, 95% ci: 0.61, 1.14).Conclusion.The high expression of ki67, vegf-a, and vegf-c significantly increases the risk of lymph node metastasis in nsclc, while the vegf-d expression has no correlation with lymph node metastasis.The expression levels of ki67, vegf-a, and vegf-c show a good potential for lymph node metastasis prediction.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Meta-Analysis;
Correlation between Carotid Stenosis Degree and Blood Pressure Variability in Patients with Carotid Stenosis

Carotid artery stenosis is one of the most serious diseases that endanger human health in contemporary times.It is a frequently occurring and common disease of the middle-aged and elderly people.Its incidence is increasing year by year, bringing a heavy economic burden to society and families.Whether there is a relationship between the degree of carotid artery stenosis and blood pressure variability is less studied.Aims.To investigate the correlation between the degree of carotid stenosis and blood pressure variability in patients with carotid stenosis.Materials and methods.A total of 200 patients with carotid artery stenosis who were treated in our hospital from january 2017 to january 2020 were selected as the subjects of prospective study and were divided into mild stenosis according to the degree of carotid stenosis (carotid artery stenosis rate was 0-50%), moderate stenosis (carotid artery stenosis rate was between 50% and 70%), severe stenosis (carotid artery stenosis rate ≧ 70 % ), and the control group with 50 cases each.The correlations between the hemodynamics, the degree of carotid artery stenosis, and blood pressure variability in patients with carotid artery stenosis were analyzed.Results.The levels of 24h ssd, 24h dsd, d ssd, d dsd, and n ssd in the mild stenosis group and moderate stenosis group were significantly higher than those in the control group.In the stenosis group, the levels of 24h ssd, 24h dsd, d ssd, d dsd, and n ssd in the severe stenosis group were significantly higher than those in the moderate stenosis group, with statistical significance ( p &lt; 0.05 ).The levels of psv, edv, and mv in the mild stenosis group and moderate stenosis group were lower than those in the control group, while the pi and ri indexes were higher than those in the control group.Pi and ri levels were significantly higher than those in the mild stenosis group and moderate stenosis group ( p &lt; 0.05 ).Logistic analysis showed that edv ( p = 0.001 , or = 2.245 , 95 % ci = 1.638 ~ 3.078 ), ssd ( p = 0.014 , or = 0.725 , 95 % ci = 0.528 ~ 0.996 ), and psv ( p = 0.001 , or = 1.970 , 95 % ci = 1.300 ~ 2.990 ) were closely related to the degree of carotid artery stenosis.Conclusion.Hemodynamics and blood pressure variability are related to the severity of carotid stenosis, which provides a reference and basis for clinical treatment of carotid stenosis.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Correlation Analysis between the Characteristics of Helicobacter pylori Resistance and the Antibiotic Use Density in a Hospital from 2012 to 2018

To explore the correlation between the resistance characteristics of helicobacter pylori (hp) and antibiotic use density (aud) in a hospital from 2012 to 2018.Methods.Hp strains isolated from chinese pla general hospital from 2012 to 2018 were collected to analyze the drug resistance of clarithromycin, levofloxacin, amoxicillin, and metronidazole, and their correlation with the aud of the outpatient department and inpatient department was analyzed, respectively.Results.From 2012 to 2018, metronidazole-resistant strains accounted for the largest proportion, followed by clarithromycin and levofloxacin, and amoxicillin-resistant strains accounted for the least.In 2012–2018, the resistance rate of clarithromycin, levofloxacin, amoxicillin, and metronidazole has basically increased year by year; from 2012 to 2018, the highest outpatient aud in a hospital was amoxicillin, followed by clarithromycin and levofloxacin, metronidazole was the lowest, and the inpatient aud from high to low was levofloxacin, metronidazole, amoxicillin, and clarithromycin.The drug resistance rate of hp in the hospital from 2012 to 2018 was positively correlated with the aud of clarithromycin (r = 0.884, p = 0.017 ) and levofloxacin (r = 0.934, p = 0.002 ) in the outpatient department.Conclusions.Helicobacter pylori has the strongest resistance to metronidazole and the worst resistance to amoxicillin in the hospital from 2012 to 2018, being related to the intensity of clarithromycin and levofloxacin in the outpatient department.It may provide certain reference significance for the clinical treatment of helicobacter pylori.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
Contemporary Advertising Text Art Design and Effect Evaluation by IoT Deep Learning under the Smart City

This work intends to solve the problem that the current artistic typeface generation methods rely too much on manual intervention, lack novelty, and the single font local feature and the global feature extraction method cannot fully describe the font features.Firstly, it proposes a handwritten word recognition model based on generalized search trees (gist) and the pyramid histogram of oriented gradient (phog).The local features and global features of the font are fused.Secondly, a model of automatic artistic typeface generation based on generative adversarial networks (gan) is constructed, which can use hand-drawn fonts to automatically generate artistic typefaces in the desired style through training as needed.Finally, the generation of the huaniao typeface is used as an example.By constructing the dataset, the effectiveness of the two models is verified.The experimental results show the following: (1) the proposed handwritten character recognition model based on gist and phog has a higher recognition rate of different fonts than the single gist and phog features by more than 5.8%.The total recognition time is reduced by more than 49.4%, and the performance is improved significantly.(2) compared with other popular algorithms, the constructed gan-based automatic artistic typeface generation model has the best quality of the generation of huaniao on both the pencil sketch and the calligraphy character image dataset.Models have broad application prospects in contemporary advertising text art design.This study aims to provide important technical support for the automation of contemporary advertising text art design and the improvement of overall efficiency.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Construction of Real Estate Debt Crisis Early Warning Model Based on RBF Neural Network

The current market economic environment is constantly changing, and real estate companies are constantly facing various risks in the course of their operations, which have created some obstacles to real estate companies’ normal financial activities, and the occurrence of a debt crisis may reduce the company’s expected benefits.If real estate companies can identify debt risks early on and take effective steps to avoid them, they will have a better chance of avoiding debt problems.Therefore, this study introduces rbf neural network technology to construct a new real estate debt crisis early warning model.This study selects 20 indicators, constructs the financial early warning index system of listed companies, collects the financial data of 86 real estate listed companies from 2016 to 2020, uses the principal component analysis method to reduce the dimension of the collected financial data, and uses the reduced dimension data to construct the real estate debt crisis early warning model of rbf neural network to realize the real estate debt crisis early warning.The empirical results show that the early warning model constructed in this study can effectively warn the real estate debt crisis, effectively analyze the development trend of real estate companies, help to better prevent the debt crisis of real estate enterprises, and improve the comprehensive benefits of real estate enterprises.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Construction of Computer Microscope Image Segmentation Model Based on Fourth-Order Partial Differential Equation Smoothing

In order to solve the problem of image noise, the author proposes a computer microscope image segmentation model based on the smoothing of fourth-order partial differential equations.On the basis of the functional describing the smoothness of the image by the directional curvature modulus, the author deduces a fourth-order partial differential equation (pde) image noise reduction model, while effectively reducing noise, the edges are well preserved.The processing result of this method is a piecewise linear image, and there is a step in the gradient at the edge of the target.Taking advantage of this feature of the noise reduction results, the author proposes a new geodesic active contour model.The experimental results show that the reference method directly segments the results, iterates 10 times, and takes 160.721 seconds.Using the noise reduction model in the paper to preprocess and then using the reference method to segment the result, iterating 8 times, it takes 32.347 seconds.Conclusion.The new model is not only stable but also has strong contour extraction ability and fast convergence speed.

Journal: Scanning (2022)
Publication types: Research Article;
Concurrent Hearing and Genetic Screening among Newborns in Ningbo, China

To detect the carrier rates of deafness gene variants in populations in ningbo and analyze the risk of hereditary hearing loss through concurrent hearing and genetic screening tests.Methods.Two thousand one hundred and seventy-four newborns were enrolled from november 2018 to august 2019.All subjects underwent hearing screening and newborn deafness genetic screening with 15 variants in 4 genes, and the positive sites were simultaneously verified by sequencing.Results.The total carrier rate of genetic variants in ningbo reached 4.32%, when gjb2 c.235del c was the variant with the highest prevalence (2.12%), approximately accounting for 48.9% of the total carrier frequency.The carrier frequency of slc26a4 c.919-2a&gt;g was 0.87%, while the most common variant in mitochondrial dna (mt dna) mt-rnr1 gene was m.1555a&gt;g, and its carrier frequency was 0.184%.In the oae testing, 92 newborns passing hearing screening were tested positively for variants in 4 genes, and 2 of 42 newborns who failed in the first hearing test were found to mutate in 4 genes.Conclusion.Herein, the results concerning the carrier rates for deafness gene mutations of ningbo population are reported.Our study is beneficial to the insight into the deafness genomic epidemiology for deafness genes in ningbo population and provides the reference for healthcare in ningbo.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;