syedzayyan/paper_mill_benchmark huggingface dataset:
A Nomogram Predicting the Prognosis of Renal Cell Carcinoma Patients with Lung Metastases

The optimal tool for predicting the survival of renal cell carcinoma (rcc) patients with lung metastases remains controversial.Methods .We selected patients diagnosed with rcc and lung metastases, from 2010 to 2015, from the surveillance, epidemiology, and end results (seer) database.After the selection of inclusion criteria and exclusion criterion, the rest of the patients were incorporated into model analysis.Least absolute shrinkage and selection operator (lasso) regression was used to select the most important features for construction of a nomogram predicting cancer‐specific survival.A calibration plot and the concordance index ( c ‐index) were used to estimate nomogram efficacy in a validation cohort.The association between important factors selected by lasso regression, and prognosis was assessed by the kaplan‐meier (km) survival curve.The receiver operating characteristic (roc) curves were drawn to compare sensitivity and specificity between the nomogram we built and the tnm stage‐based model.Results .A total of 1,369 patients met the inclusion criteria, but not the exclusion criteria.The lasso regression model reduced 15 features to seven potential predictors of survival, including tumor grade, the extent of surgery, n and t status, histological profile, and brain and bone metastasis status.Such features had good discrimination in the km survival curves.The nomogram showed excellent discriminatory power ( c ‐index, 0.71; 95% confidence interval: 0.70 to 0.72) and good calibration in terms of both 1‐ and 2‐year cancer‐specific survival.The nomogram showed great discriminatory power ( c ‐index 0.68) and adequate calibration when applied to the validation cohort.The areas under the curve (aucs) of nomogram were 0.767 and 0.780, respectively, and the aucs of tnm stage were 0.617 and 0.618 at 1 and 2 years, respectively.Conclusions .Our nomogram might play a major role in predicting the cancer‐specific survival of rcc patients with lung metastases.

Journal: BioMed Research International (2021)
Publication types: Research Article;
Design of PPP Project under Computer Network and Different Capital Structures

In order to address the applicability of the ppp project auction system in the current market, this paper studies the mechanism and related models of ppp projects under different capital structures and improved approach of selecting items only by price, using computer network systems and heuristic algorithms.The electronic reverse auction (era) of ppp projects under different capital structures under the diversified environment is established.This paper selects the traditional government procurement model as the reference group.The era of ppp projects under the computer network background and different capital structures was selected as the observation group, through the comparative analysis of the procurement cost, the negotiation time cost, the supplier selection range, the project construction efficiency, the project cost, and other aspects.The correlation and feasibility were also tested by a bivariate t test.The results suggest that the system automates ppp project selection, it can realize the optimization of each comprehensive level of the survey project, meet the procurement needs of different funds, improve the procurement efficiency, and reduce procurement costs; in the context of computer networks, the era of ppp projects under different capital structures can effectively save the cost of buyers and bidders and improve cost-saving efficiency.Different from the traditional auction mechanism, it is no longer an auction.Even shopping around can make the auctioneer or bidder get best interests.The era mechanism developed under the background of this new computer network provides new possibilities and impetus for the further development of the auction mechanism.

Journal: Mobile Information Systems (2022)
Publication types: Research Article;
A Multimodel Fusion Method for Cardiovascular Disease Detection Using ECG

Electrocardiogram (ecg) is an important diagnostic tool that has been the subject of much research in recent years.Owing to a lack of well-labeled ecg record databases, most of this work has focused on heartbeat arrhythmia detection based on ecg signal quality.Approach.A record quality filter was designed to judge ecg signal quality, and a random forest method, a multilayer perceptron, and a residual neural network (resnet)-based convolutional neural network were implemented to provide baselines for ecg record classification according to three different principles.A new multimodel method was constructed by fusing the random forest and resnet approaches.Main results.Owing to its ability to combine discriminative human-crafted features with resnet deep features, the proposed new method showed over 88% classification accuracy and yielded the best results in comparison with alternative methods.Significance.A new multimodel fusion method was presented for abnormal cardiovascular detection based on ecg data.The experimental results show that separable convolution and multiscale convolution are vital for ecg record classification and are effective for use with one-dimensional ecg sequences.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
A Model of Spatial Cell Development in Rat Hippocampus Based on Artificial Neural Network

Physiological studies have shown that the hippocampal structure of rats develops at different stages, in which the place cells continue to develop during the whole juvenile period of rats and mature after the juvenile period.As the main information source of place cells, grid cells should mature earlier than place cells.In order to make better use of the biological information exhibited by the rat brain hippocampus in the environment, we propose a position cognition model based on the spatial cell development mechanism of rat hippocampus.The model uses a recurrent neural network with parametric bias (rnnpb) to simulate changes in the discharge characteristics during the development of a single stripe cell.The oscillatory interference mechanism is able to fuse the developing stripe waves, thus indirectly simulating the developmental process of the grid cells.The output of the grid cells is then used as the information input of the place cells, whose development process is simulated by bp neural network.After the place cells matured, the position matrix generated by the place cell group was used to realize the position cognition of rats in a given spatial region.The experimental results show that this model can simulate the development process of grid cells and place cells, and it can realize high precision positioning in the given space area.Moreover, the experimental effect of cognitive map construction using this model is basically consistent with the effect of rat slam, which verifies the validity and accuracy of the model.

Journal: Journal of Healthcare Engineering (2021)
Publication types: Research Article;
A Method for Expanding the Training Set of White Blood Cell Images

In medicine, the count of different types of white blood cells can be used as the basis for diagnosing certain diseases or evaluating the treatment effects of diseases.The recognition and counting of white blood cells have important clinical significance.But the effect of recognition based on machine learning is affected by the size of the training set.At present, researchers mainly rely on image rotation and cropping to expand the dataset.These methods either add features to the white blood cell image or require manual intervention and are inefficient.In this paper, a method for expanding the training set of white blood cell images is proposed.After rotating the image at any angle, canny is used to extract the edge of the black area caused by the rotation and then fill the black area to achieve the purpose of expanding the training set.The experimental results show that after using the method proposed in this paper to expand the training set to train the three models of res net, mobile net, and shuffle net, and comparing the original dataset and the method trained by the simple rotated image expanded dataset, the recognition accuracy of the three models is obviously improved without manual intervention.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
A Data-Efficient Framework for the Identification of Vaginitis Based on Deep Learning

Vaginitis is a gynecological disease affecting the health of millions of women all over the world.The traditional diagnosis of vaginitis is based on manual microscopy, which is time-consuming and tedious.The deep learning method offers a fast and reliable solution for an automatic early diagnosis of vaginitis.However, deep neural networks require massive well-annotated data.Manual annotation of microscopic images is highly cost extensive because it not only is a time-consuming process but also needs highly trained people (doctors, pathologists, or technicians).Most existing active learning approaches are not applicable in microscopic images due to the nature of complex backgrounds and numerous formed elements.To address the problem of high cost of labeling microscopic images, we present a data-efficient framework for the identification of vaginitis based on transfer learning and active learning strategies.The proposed informative sample selection strategy selected the minimal training subset, and then the pretrained convolutional neural network (cnn) was fine-tuned on the selected subset.The experiment results show that the proposed pipeline can save 37.5% annotation cost while maintaining competitive performance.The proposed promising novel framework can significantly save the annotation cost and has the potential of extending widely to other microscopic imaging applications, such as blood microscopic image analysis.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;
A Computational Model of Blood D-Dimer, Cystatin C, and CRP Levels Predicts the Risk of Intracranial Aneurysms and their Rupture

The aim of this study is to construct a computational model of blood d-dimer, cystatin c, and crp levels and to predict the risk of intracranial aneurysms and their rupture.Methods.A total of 69 intracranial aneurysms patients were selected as the case group, including 28 cases in the ruptured group and 41 cases in the unruptured group.Another 64 non-intracranial aneurysm patients were selected as the control group.The detection results of serum d-dimer, cystatin c, and crp were collected.The logistic regression computational model was used to analyze the occurrence and risk factors of intracranial aneurysms.The receiver operating curves (roc) of serum d-dimer, cystatin c, and c reactive protein (crp) levels for predicting intracranial aneurysms and their rupture were drawn, and the area under the curve (auc), sensitivity, and specificity were calculated.Results.The serum levels of d-dimer, cystatin c, and crp in patients with intracranial aneurysms were significantly higher than those in the control group and the differences were statistically significant p &lt; 0.05 .The serum levels of d-dimer, cystatin c, and crp in patients with ruptured intracranial aneurysms were higher than those in patients with unruptured intracranial aneurysms, and the differences were also statistically significant p &lt; 0.05 .The combined detection of serum d-dimer, cystatin c, and crp levels has a higher auc (0.9014) for predicting intracranial aneurysms and higher auc (0.9412) for predicting ruptured intracranial aneurysms than d-dimer (0.7118 and 0.8750, respectively), cystatin c (0.6489 and 0.6180, respectively), and crp (0.7764 and 0.6551, respectively) independent detection; the combined detection had a sensitivity of 93.75% and 87.80 for predicting the occurrence and rupture of intracranial aneurysms, and the specificity was 68.12% and 92.86%, respectively.Conclusion.The combined detection of serum d-dimer, cystatin c, and crp levels is a very valuable indicator for predicting the occurrence and rupture of intracranial aneurysms, and combined detection can provide scientific evidence-based guidance for clinical prediction of the occurrence and rupture of intracranial aneurysms.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
A Computational Framework to Identify Transcriptional and Network Differences between Hepatocellular Carcinoma and Normal Liver Tissue and Their Applications in Repositioning Drugs

Hepatocellular carcinoma (hcc) is one of the most common and lethal malignancies worldwide.Although there have been extensive studies on the molecular mechanisms of its carcinogenesis, fda‐approved drugs for hcc are rare.Side effects, development time, and cost of these drugs are the major bottlenecks, which can be partially overcome by drug repositioning.In this study, we developed a computational framework to study the mechanisms of hcc carcinogenesis, in which drug perturbation‐induced gene expression signatures were utilized for repositioning of potential drugs.Specifically, we first performed differential expression analysis and coexpression network module analysis on the hcc dataset from the cancer genome atlas database.Differential gene expression analysis identified 1,337 differentially expressed genes between hcc and adjacent normal tissues, which were significantly enriched in functions related to various pathways, including α ‐adrenergic receptor activity pathway and epinephrine binding pathway.Weighted gene correlation network analysis (wgcna) suggested that the number of coexpression modules was higher in hcc tissues than in normal tissues.Finally, by correlating differentially expressed genes with drug perturbation‐related signatures, we prioritized a few potential drugs, including nutlin and eribulin, for the treatment of hepatocellular carcinoma.The drugs have been reported by a few experimental studies to be effective in killing cancer cells.

Journal: BioMed Research International (2021)
Publication types: Research Article;
A Cohort Study to Compare Effects between Ulcer- and Nonulcer-Related Nonvariceal Upper Gastrointestinal Bleeding

The aim of this study was to better understand the characteristics and etiology of acute nonvariceal upper gastrointestinal bleeding (anvugib) in recent years in this region and to provide evidence-based medical evidence.Methods.100 patients with acute nonvariceal upper gastrointestinal bleeding (anvugib) who met the clinical diagnostic criteria of anvugib admitted to suzhou first people’s hospital from january 2017 to december 2021 were analyzed, as well as the age difference and change rule.According to age, 100 patients were divided into young (18-39 years), middle-aged (40-59 years), and elderly (60 years and above), and the differences in the three groups were compared.The etiology was confirmed by endoscopic examination and was recorded one by one in a well-designed anvugib case data registration form.Statistical software spss 23.0 was used for analysis.Results.Gastric ulcer was the main cause in the elderly group (50.0%), duodenal ulcer was the main cause in the middle and young groups, and gastrointestinal cancer (7.1%) and marginal ulcer (2.3%) in the elderly group were higher than those in the young group.Nonsteroidal anti-inflammatory drugs (52.3%) were the main inducement in the elderly group, which was significantly higher than in the middle-aged group (13.1%) and the young group (5%) ( p &lt; 0.01 ).Drinking, fatigue, and emotional excitement led to a higher proportion in the middle-aged group and the young group, in comparison to the elderly group ( p &lt; 0.01 ).Conclusion.Peptic ulcer is the most common cause of acute nonvariceal upper gastrointestinal bleeding, followed by acute gastric mucosal lesions and upper digestive system tumors, compared with nonulcer.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
A Cohort Study on the Safety and Efficacy of Warfarin and Rivaroxaban in Anticoagulant Therapy in Patients with Atrial Fibrillation Study

To observe the safety and efficacy of warfarin and rivaroxaban in anticoagulation therapy in patients with atrial fibrillation (af).Methods .A total of 96 patients with af treated in our hospital from june 2019 to february 2021 were enrolled in this study.According to the different modes of drug administration, the patients were divided into the warfarin group and rivaroxaban group.Demographic and clinical data such as age, body weight, and previous drug use were collected.The blood routine, liver and kidney function, blood coagulation routine, and cardiac color ultrasound were accessed.The valvular atrial fibrillation and anticoagulant taboos were excluded, and the risk of embolism and bleeding was evaluated.Among them, 48 patients in the warfarin group were given warfarin once a day, and the international ratio (inr) was used to adjust the dose, and the inr was controlled between 2.0 and 3.0.In contrast, 48 patients in the rivaroxaban group received a fixed dose of rivaroxaban 20 mg or 15 mg once a day.After administration, regular telephone or outpatient follow‐up was given once a month, to monitor patients’ drug compliance and ask if there was bleeding, and to detect blood routine, urine routine, fecal routine+occult blood, and liver and kidney function.In addition, at the beginning of 3, 6, and 12 months of follow‐up, each patient was given cardiac color doppler ultrasound, peripheral vascular color ultrasound, and brain ct to determine whether there were mural thrombosis, stroke, and peripheral arterial thromboembolism.The inr attainment rate, coagulation index, thromboembolism, bleeding, and adverse reactions were compared between the two groups.Results .There was no significant difference in serum dmurd and nt‐pro bnp levels between the two groups before treatment and 3, 6, and 9 months after treatment.There was no significant difference in the number of venous embolism, pulmonary embolism, cerebral embolism, and total embolism between the two groups ( p &gt; 0.05).There was no significant difference in the number of mild, moderate, and severe bleeding between the two groups ( p &gt; 0.05), but the total number of bleeding in the rivaroxaban group was lower than that in the warfarin group ( p &lt; 0.05).During the treatment, side effects such as nausea and vomiting, elevated transaminase, glutamyl transpeptidase, and diarrhea occurred between the two groups, and there was no significant difference in the number of adverse reactions between the two groups ( p &gt; 0.05).Conclusion .Compared with warfarin, rivaroxaban anticoagulant therapy has the same advantage in tolerance and prevention of thromboembolism in patients with af, but rivaroxaban can effectively reduce the risk of bleeding in patients with af.

Journal: BioMed Research International (2022)
Publication types: Clinical Study;
A Clinical Decision Support System (CDSS) for Unbiased Prediction of Caesarean Section Based on Features Extraction and Optimized Classification

Nowadays, caesarean section (cs) is given preference over vaginal birth and this trend is rapidly rising around the globe, although cs has serious complications such as pregnancy scar, scar dehiscence, and morbidly adherent placenta.Thus, cs should only be performed when it is absolutely necessary for mother and fetus.To avoid unnecessary cs, researchers have developed different machine-learning- (ml-) based clinical decision support systems (cdss) for cs prediction using electronic health record of the pregnant women.However, previously proposed methods suffer from the problems of poor accuracy and biasedness in ml.To overcome these problems, we have designed a novel cdss where random oversampling example (rose) technique has been used to eliminate the problem of minority classes in the dataset.Furthermore, principal component analysis has been employed for feature extraction from the dataset while, for classification purpose, random forest (rf) model is deployed.We have fine-tuned the hyperparameter of rf using a grid search algorithm for optimal classification performance.Thus, the newly proposed system is named rose-pca-rf and it is trained and tested using an online cs dataset available on the uci repository.In the first experiment, conventional rf model is trained and tested on the dataset while in the second experiment, the proposed model is tested.The proposed rose-pca-rf model improved the performance of traditional rf by 4.5% with reduced time complexity, while only using two extracted features through the pca.Moreover, the proposed model has obtained 96.29% accuracy on training data while improving the accuracy of 97.12% on testing data.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
A Blumgart Anastomosis-Based Half-Invagination Pancreaticoenterostomy with Better Applicability to Laparoscopy and Lower Incidence of Pancreatic Leakage

The blumgart anastomosis (ba) is one of the safest anastomoses for pancreatic stump reconstruction.The incidence of postoperative pancreatic fistula (popf) and postoperative complications is low.However, how to make laparoscopic pancreaticoenterostomy easier and safer is still a topic to be discussed.Methods .The data of patients who underwent laparoscopic pancreaticoduodenectomy (pd) from april 2014 to december 2019 were analyzed retrospectively.Results .Half‐invagination anastomosis was performed in 20 cases (hi group), and the cattell‐warren anastomosis was carried out in 26 cases (cw group).The amount of intraoperative bleeding, operation time, and postoperative catheterization time in the hi group was significantly less than those in the cw group.Besides, the number of patients at the clavien‐dindo grade iii and above in the hi group was significantly less than that in the control group.Moreover, the incidence of popf in the hi group was significantly lower than that in the cw group.Furthermore, fistula risk score (frs) analysis showed that there was no high‐risk group, and the highest risk in the medium‐risk group was pancreatic leakage.In addition, the incidence of pancreatic leakage in the hi group and cw group was 7.7% and 46.67%, respectively, while the incidence of pancreatic leakage in the hi group was significantly lower than that in the cw group.Conclusions .The half‐invagination pancreaticoenterostomy based on the blumgart anastomosis should have good applicability under laparoscopy and could effectively reduce the incidence of postoperative pancreatic leakage.

Journal: Computational and Mathematical Methods in Medicine (2023)
Publication types: Research Article;
3D Finite Element Analysis of Seismic Response of Rigid Pile Composite Foundation with Microprobe Group

In order to study the seismic performance of the rigid pile composite foundation, a three-dimensional finite element analysis of the seismic response of the rigid pile composite foundation with microprobe group was proposed.The three-dimensional finite element method is used to analyze the dynamic response law of pile group rigid pile composite foundation under the action of the earthquake, especially the internal force response of the pile body.It is worth noting that when the internal force response of pile decreases significantly, the maximum internal force of the whole pile is also significantly smaller than the maximum internal force of pile foundation.However, when the pile body is located on a layered foundation and the modulus of adjacent soil layers differs greatly, the earthquake action will cause the pile body to generate a large internal force.The seismic performance of the rigid pile composite foundation is feasible, and it can be extended and applied to the similar seismic performance test of other composite foundations.

Journal: International Journal of Analytical Chemistry (2022)
Publication types: Research Article;