syedzayyan/paper_mill_benchmark huggingface dataset:
18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival

Colon cancer is a type of cancer that begins in the large intestine.In the process of efficacy evaluation, postoperative recurrence prediction and metastasis monitoring of colon cancer, traditional medical image analysis methods are highly dependent on the personal ability of the doctors.In the process of patient treatment, it not only increases the workload and work pressure for doctors, but also has some problems with traditional medical image analysis methods.Moreover, the traditional medical image analysis methods have problems such as insufficient prediction accuracy, slow prediction speed, and the risk of errors in prediction.When analyzing 18f-fdg pet/ct images by traditional medical image analysis methods, it is easy to cause problems such as untimely treatment plans and errors in diagnosis, which will adversely affect the survival of colon cancer patients.Although 18f-fdg pet/ct images have certain advantages in image clarity and accuracy compared with traditional medical imaging methods, the analysis method based on 18f-fdg pet/ct images also has certain effects in predicting the survival of colon cancer patients, but there are still many shortcomings: the 18f-fdg pet/ct image analysis method overly relies on the technical advantages of 8f-fdg pet/ct images; in the analysis and prediction of image data, it has not gotten rid of the dependence on the personal medical quality of the doctors; traditional medical image analysis methods are still used when analyzing and predicting images; there is no breakthrough in image analysis effects.In order to solve these problems, this paper combined deep learning theory, using three algorithms of the improved rbm algorithm, image feature extraction method based on deep learning, and regression neural network to analyze and predict 18f-fdg pet/ct images, and applied some algorithms to analyze and predict 18f-fdg pet/ct images, and also established a deep learning-based 18f-fdg pet/ct image survival analysis prediction model.Four aspects survival prediction accuracy, survival prediction speed, survival prediction precision, and physician satisfaction were studied through this model.The research results have shown that compared with traditional medical image analysis methods, the prediction accuracy of 18f-fdg pet/ct image survival analysis prediction model based on deep learning is improved by 0.83%, and the prediction speed is improved by 3.42%, as well as the prediction precision increased by 6.13%.The research results show that the deep learning-based 18f-fdg pet/ct image survival analysis prediction model established in this paper is of great significance to improve the survival rate of colon cancer patients, and also promotes the development of the medical industry.

Journal: Contrast Media & Molecular Imaging (2023)
Publication types: Research Article;
X-Ray Small Target Security Inspection Based on TB-YOLOv5

Security inspection is extremely important for the safety of public places.In this research, we are trying to propose a novel algorithm and investigated theoretically in the x-ray dataset, which can optimize the relative low detection accuracy and the latent omission detection of smaller objects when using you only look once version 5 (yolov5).For one side, the transform detection network is selected to be added at the bottom layer of backbone structure to avoid the loss of useful information during sequential calculation.On another side, we attempt to adjust the existing panet structural elements of the model, including their connections and other related parameters to improve the detection performance.We integrate an efficient bi fpn with the ca mechanism, which can enhance feature extraction, and named it attention-bi fpn.Experimental consequences demonstrate that the detection accuracy of the proposed model, which we name “tb-yolov5,” has obvious advantages in check performance compared with the mainstream one-stage object detection models.Meanwhile, compared with yolov5, the data results display an improvement of up to 14.9%, and the average precision at 0.5 iou even reached 23.4% higher in the region of small object detection.Our purpose was to explore the potential of changing a popular detection algorithm such as yolo to address specific tasks and provide insights on how specialized adjustments can influence the detection of small objects.Our work can supply an effective method of enhancing the performance of x-ray security inspection and show promising potential for deep learning in related fields.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
X-Ray Film under Artificial Intelligence Algorithm in the Evaluation for Nursing Effect of Gamma Nail Internal Fixation in Elderly Patients with Intertrochanteric Fracture of Femur

The aim of this work was to explore the effects of gamma nail internal fixation for intertrochanteric fracture of femur by x-ray film classification and recognition method based on artificial intelligence algorithm.The study subjects were 100 elderly patients with intertrochanteric fracture of femur admitted to hospital.The cases were diagnosed as elderly (over 60 years old) femoral intertrochanteric fractures by x-ray or ct.They were divided into two groups, with 50 persons in each group: one group used the x-ray film evaluation image guidance based on the artificial intelligence algorithm (research group), and the other group did not use algorithmic guidance (control group).The results showed that the segmentation effect of the proposed algorithm was similar to the gold standard segmentation result, indicating that the algorithm was effective and feasible in the segmentation of fractures and bones.The global level set algorithm was set as the control.The ultimate measurement accuracy (uma) value of the algorithm group was ( 1.77 ± 0.22 ), and the uma value of the global level set algorithm group was ( 3.42 ± 0.36 ), indicating that the image processed by the algorithm group had obvious numerical effect, high accuracy, and good retention of details.The operation time, intraoperative blood loss, incision length, hospital stay, weight-bearing time, and fracture healing time of the two groups were all better than those of the control group.One month after surgery, the harris score of the algorithm group was 67, and that of the control group was 51, with a 16-point difference between the two groups ( p &lt; 0.05 ).The patient had less pain and fast recovery speed, indicating that it was a good way to treat elderly intertrochanteric fractures with the nursing effect of x-ray gamma nail internal fixation based on an artificial intelligence algorithm.The artificial intelligence algorithm not only can be applied to the gamma nail internal fixation of elderly patients with intertrochanteric fractures but also can be applied to the x-ray image processing of other fractures and other surgical methods to provide effective treatment for fracture patients.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Wild Bitter Melon Extract Abrogates Hypoxia-Induced Cell Death via the Regulation of Ferroptosis, ER Stress, and Apoptosis in Microglial BV2 Cells

Microglial cells are well-known phagocytic cells that are resistant to the central nervous system (cns) and play an important role in the maintenance of cns homeostasis.Activated microglial cells induce neuroinflammation under hypoxia and typically cause neuronal damage in cns diseases.In this study, we propose that wild bitter melon extract (wbm) has a protective effect on hypoxia-induced cell death via regulation of ferroptosis, er stress, and apoptosis.The results demonstrated that hypoxia caused microglial bv-2 the accumulation of lipid ros, ferroptosis, er stress, and apoptosis.In this study, we investigated the pharmacological effects of wbm on bv-2 cells following hypoxia-induced cell death.The results indicated that wbm reversed hypoxia-downregulated antiferroptotic molecules gpx4 and slc7a11, as well as upregulated the er stress markers chop and bip.Moreover, wbm alleviated hypoxia-induced apoptosis via the regulation of cleaved-caspase 3, bax, and bcl-2.Our results suggest that wbm may be a good candidate for preventing cns disorders in the future.

Journal: Evidence-Based Complementary and Alternative Medicine (2022)
Publication types: Research Article;
Where Does Digital Entrepreneurship Go? A Review Based on a Scientific Knowledge Map

There is more and more digital entrepreneurship emerging in practice, but research on it is rare and scattered, meaning that a review of digital entrepreneurship is important and necessary.Based on a data set covering 19 years of research, from 2003 to 2021, this article reviews 469 available articles from the web of science core collection.Using a scientific knowledge map, it divides digital entrepreneurship research into two stages, namely the “emerging stage” (2003–2017) and the “booming stage” (2018–2021).Research developed slowly in the emerging stage, focusing on the definition of digital entrepreneurship, the influence of digital technology, and antecedents of digital entrepreneurship.In the booming stage, however, digital entrepreneurship research grew explosively.This article sorts out the topics from three aspects, that is, organizational behavior, digital entrepreneurial ecosystem, and business model innovation.Longitudinal research, multi-case studies, mixed methods, and quantitative studies become mainstream, replacing the earlier single-case studies and conceptual analyses.The frontiers of research on digital entrepreneurship focus on digital entrepreneurial ecosystems, business model innovation, digital academic entrepreneurship, digital transformation, and the antecedents of digital entrepreneurship.This article proposes four future directions, including the interaction of digital entrepreneurship elements, the process of digital entrepreneurship with a dynamic perspective, digital entrepreneurship research at the community level, and digital entrepreneurship research in different contexts.

Journal: Mobile Information Systems (2022)
Publication types: Review Article;
Water Environment Governance of Urban and Rural Spaces Integrating Natural Ecological Landscape Design Method

The water environment is one of the basic elements that constitute the environment.It is an important place for the survival and development of human society, and it is also the most seriously disturbed and damaged area by humans.The pollution and destruction of water environment has become one of the major environmental problems in the world today.The essence of urban water space landscape design under the concept of integrating people’s ecological design is the ecological landscape design of urban water spaces, while the development of ecological landscape design in the field of urban water space landscape design is still in its infancy, and the interpretation of its concept is also different.The ecological design of the landscape reflects a new dream of human beings, a new aesthetics and value: the true cooperative and fraternal relationship between man and nature.At present, the ecological design of urban water space landscape has not put forward a more accurate concept, clear principles and standards, and a complete and systematic theoretical basis, which requires further research, discussion, and continuous practice by this generation of designers to improve it.To this end, this paper proposed a research method on the integration of water environment governance in urban and rural spaces with natural ecological landscape design.This paper mainly talked about the status quo of water environment and its network sensor algorithm research and analyzed its coverage area one by one.Then, the water quality extraction is introduced in detail.And finally, the data analysis of the beijing river waters, the analyzer rainfall, water quality, and so on are carried out in the experimental part.It could be seen from the experimental results that there were currently 22 reclaimed water plants in six urban areas of beijing, with a daily water treatment capacity of 4.08 million cubic meters and a sewage treatment rate of 98%.As of 2016, 440 million cubic meters of reclaimed water has been reused.With the commissioning of the new reclaimed water system, the proportion of reclaimed water in the river and lake environment will continue to increase.

Journal: Journal of Environmental and Public Health (2022)
Publication types: Research Article;
Visual Sensing Technology for Digital Image-Oriented Public Art Design

With the development of computer software technology, computer image processing software has become increasingly significant in the public art design process.It can help with graphic design inventiveness and color presentation, as well as improve the aesthetics of public art design.This study aims to analyze the use of digital image synthesis and visual sensing techniques in public art design, as well as to use dongba paintings, which reflects chinese culture, as image fusion research objects.The dongba painting’s line drawing is modeled and drawn, and an element library is created.The characteristic information of dongba paintings is extracted using line integration convolution (lic) algorithm.The background texture elements of the image are fused using image quilting texture’s improved synthesis algorithm.To improve the image effect of the linked dongba paintings, a local color transfer algorithm based on color transfer rights is presented.The results show that the optimized synthesis algorithm of image quilting textures can achieve the same texture synthesis effect as the original algorithm.The method can meet the needs of real-world applications while also significantly improving the original technique’s performance.The synthesis time is reduced by 87.67%, and the image recognition accuracy of the local color transfer algorithm reaches 88.9%.Compared with other algorithms, the recognition accuracy is improved by 6.4%.The proposed digital image synthesis technique can create good images with different foreground and backdrop combinations and can provide a diverse visual expression.This contributes to public art’s visual production.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
Virtual Digital Communication Feature Fusion Based on Virtual Augmented Reality

In order to have a deeper understanding of the integration of virtual digital communication characteristics, it is studied and combined with virtual augmented reality technology.The progress of science and technology has promoted the development and progress of virtual reality technology.In recent years, virtual reality technology has been more and more widely used in digital media art creation and plays an important role in improving the quality of digital media art.This study introduces digital media art and virtual reality technology and analyzes the specific measures and practical significance of the application of virtual reality technology in digital media art creation.As an emerging technology, virtual reality technology has certain advantages.Its application in digital media art creation can effectively make up for the shortcomings of traditional creation and realize the innovation and reform of art creation.

Journal: Security and Communication Networks (2022)
Publication types: Research Article;
VEGF Family Gene Expression as Prognostic Biomarkers for Alzheimer’s Disease and Primary Liver Cancer

To analyze the expression of vascular endothelial growth factor (vegf) in hepatocellular carcinoma (hcc) and cognitive impairment, explore the relationship between the expression of vegf family genes and prognosis of patients with hcc, and evaluate the predictive ability of vegf in cognitive impairment using computerized methods.Methods.Vegf expression in liver cancer tissues and normal tissues was analyzed using bioinformatics methods.The kaplan-meier survival analysis method was also used to analyze the relationship between vegf expression and the prognosis of patients with hcc.Furthermore, immune infiltration assessment and gene set enrichment analysis were performed.Meanwhile, the differential expression of vegf family genes between patients with alzheimer’s disease (ad) and healthy controls was also checked.Results.Based on the cancer genome atlas (tcga) database, the vegf family genes (vefga, vegfb, vegfc, and vegfd) were highly expressed in cancer tissues and were significantly associated with poor prognosis in hcc.In hcc, the vegf family genes showed significant heterogeneity in their functional and immune infiltration characteristics.Finally, vegf family genes were identified as prognostic biomarkers in ad and risk prediction markers in hcc.Conclusions.Vegf is highly expressed in patients with hcc and lowly expressed in patients with ad.Vegf has opposite opposing roles in the treatment of tumors and cognitive impairment.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Value of Ultrasonic Image Features in Diagnosis of Perinatal Outcomes of Severe Preeclampsia on account of Deep Learning Algorithm

This study is aimed at discussing the value of ultrasonic image features in diagnosis of perinatal outcomes of severe preeclampsia on account of deep learning algorithm.140 pregnant women singleton with severe preeclampsia were selected as the observation group.At the same time, 140 normal singleton pregnant women were selected as the control group.The hemodynamic indexes were detected by color doppler ultrasound.The cnn algorithm was used to classify ultrasound images of two groups of pregnant women.The differential scanning calorimetry (dsc), mean pixel accuracy (mpa), and mean intersection of union (miou) values of cnn algorithm were 0.9410, 0.9228, and 0.8968, respectively.Accuracy, precision, recall, and f 1 -score were 93.44%, 95.13%, 95.09%, and 94.87%, respectively.The differences were statistically significant ( p &lt; 0.05 ).Compared with the normal control group, the umbilical artery (ua), uterine artery-systolic/diastolic (uta-s/d), uterine artery (uta), and digital video (dv) of pregnant women in the observation group were remarkably increased; the minimum alveolar effective concentration (mca) of the observation group was obviously lower than the mca of the control group, and the differences between groups were statistically valid ( p &lt; 0.05 ).Logistic regression analysis showed that ua-s/d, ua-resistance index (ua-ri), uta-s/d, uta-pulsatility index (uta-pi), dv-peak velocity index for veins (dv-pviv), and mca-s/d were independent risk factors for the outcome of perinatal children with severe preeclampsia.In the perinatal management of severe epilepsy, the combination of the above blood flow indexes to select the appropriate delivery time had positive significance to improve the pregnancy outcome and reduce the perinatal mortality.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Using a Blur Metric to Estimate Linear Motion Blur Parameters

Motion blur is a common artifact in image processing, specifically in e-health services, which is caused by the motion of a camera or scene.In linear motion cases, the blur kernel, i.e., the function that simulates the linear motion blur process, depends on the length and direction of blur, called linear motion blur parameters.The estimation of blur parameters is a vital and sensitive stage in the process of reconstructing a sharp version of a motion blurred image, i.e., image deblurring.The estimation of blur parameters can also be used in e-health services.Since medical images may be blurry, this method can be used to estimate the blur parameters and then take an action to enhance the image.In this paper, some methods are proposed for estimating the linear motion blur parameters based on the extraction of features from the given single blurred image.The motion blur direction is estimated using the radon transform of the spectrum of the blurred image.To estimate the motion blur length, the relation between a blur metric, called nidct (noise-immune discrete cosine transform-based), and the motion blur length is applied.Experiments performed in this study showed that the nidct blur metric and the blur length have a monotonic relation.Indeed, an increase in blur length leads to increase in the blurriness value estimated via the nidct blur metric.This relation is applied to estimate the motion blur.The efficiency of the proposed method is demonstrated by performing some quantitative and qualitative experiments.

Journal: Computational and Mathematical Methods in Medicine (2021)
Publication types: Research Article;
Unsupervised Data Mining and Effect of Fast Rehabilitation Nursing Intervention in Fracture Surgery

At present, the most commonly used surgical treatment for fractures caused by external force injury is clinical, and unsupervised data mining is more advantageous in the face of the unknown format of perioperative network data.Therefore, this research aims to explore the application effect of unsupervised data mining in the concept of rapid rehabilitation nursing intervention after fracture surgery.80 patients who underwent fracture surgery in the department of orthopedics of xxx hospital were determined as the subjects, who were rolled into a research group (group r, 40 cases) and a control group (group c, 40 cases) by drawing lots.An unsupervised data mining algorithm based on unsupervised data mining for support vector machines (vdmsvms) was proposed and applied to two groups of patients undergoing perioperative fracture surgery with the rapid rehabilitation nursing intervention and basic routine nursing.The results showed that the number of important features selected by the vdmsvm algorithm (5) was obviously more than that of the compressed edge fragment sampling (cefs) algorithm (1) and the multicorrelation forward searching (mcfs) algorithm (2) ( p &lt; 0.05 ).The number of noise features screened by the vdmsvm algorithm (3) was much less in contrast to that of the cefs algorithm and the mcfs algorithm, which was 8 and 10, respectively (p &lt; 0.05).The visual analogue scale (vas) scores of the fracture site at the 4th, 8th, 12th, and 16th hour after surgery in group r were all lower than the scores in group c ( p &lt; 0.05 ).The length of hospital stay (lo hs) in group r was greatly shorter than that in group c ( p &lt; 0.05 ).After different nursing methods, the world health organization quality of life (whoqol-bref) score of patients in group r (89.64 points) was greatly higher than the score in group c (61.45 points) ( p &lt; 0.05 ).The nursing satisfaction score of group r was 92.35 ± 3.65 points, and that in group c was 2.14 ± 1.25 points, respectively ( p &lt; 0.05 ).The test results verified the effectiveness of the feature selection of the vdmsvm algorithm.The rapid rehabilitation nursing intervention was conductive to reducing the postoperative pain of fracture patients, shortening the lo hs of patients, improving the quality of life (qol) of fracture surgery patients, and increasing the patient’s satisfaction with nursing.

Journal: Journal of Healthcare Engineering (2022)
Publication types: Research Article;