syedzayyan/paper_mill_benchmark huggingface dataset:
BID-Net: An Automated System for Bone Invasion Detection Occurring at Stage T4 in Oral Squamous Carcinoma Using Deep Learning

Detection of the presence and absence of bone invasion by the tumor in oral squamous cell carcinoma (oscc) patients is very significant for their treatment planning and surgical resection.For bone invasion detection, ct scan imaging is the preferred choice of radiologists because of its high sensitivity and specificity.In the present work, deep learning algorithm based model, bid-net, has been proposed for the automation of bone invasion detection.Bid-net performs the binary classification of ct scan images as the images with bone invasion and images without bone invasion.The proposed bid-net model has achieved an outstanding accuracy of 93.62%.The model is also compared with six transfer learning models like vgg16, vgg19, res net-50, mobile net v2, dense net-121, res net-101 and bid-net outperformed over the other models.As there exists no previous studies on bone invasion detection using deep learning models, so the results of the proposed model have been validated from the experts of practitioner radiologists, s.m.s.Hospital, jaipur, india.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Automatic Detection and Classification of Epileptic Seizures in Patients with Liver Cirrhosis and Overlapping Hev Infection Based on Deep Multimodal Fusion Technology

Liver cirrhosis is a clinical chronic developmental liver disease, which is caused by long‐term or repeated effects of liver dysfunction, and there are more and more cases of epileptic seizures in patients with liver cirrhosis and hev infection.This article aims to study how to analyze epileptic seizures in patients with liver cirrhosis and overlapping hev infection based on deep multimodal fusion technology.This article proposes a deep learning neural network algorithm based on deep multimodal fusion technology, and how to use this algorithm to automatically detect and classify epileptic seizures.The data in the experiment in this article show that the prevalence of epilepsy accounts for 1% of the world's population, about 56.7 million people, and 1 in 25 people may have an epileptic seizure at some time in their lives, and in each person’s life, the probability of seizures due to various reasons is 10%.In 2016, the proportion of males with cirrhosis reached 16%, females reached 8%, and males were 8% higher than females, which is a full double.The test results show that with the increase in patients with cirrhosis and overlapping hev infection, the frequency of epileptic seizures is also getting higher and higher, indicating that the frequency of epileptic seizures has been increased in patients with cirrhosis and overlapping hev infection.Therefore, it is imperative to analyze the epileptic seizures of patients with liver cirrhosis and overlapping hev infection based on deep multimodal fusion technology.

Journal: Contrast Media & Molecular Imaging (2022)
Publication types: Research Article;
Automated Detection and Segmentation of Exudates for the Screening of Background Retinopathy

Exudate, an asymptomatic yellow deposit on retina, is among the primary characteristics of background diabetic retinopathy.Background diabetic retinopathy is a retinopathy related to high blood sugar levels which slowly affects all the organs of the body.The early detection of exudates aids doctors in screening the patients suffering from background diabetic retinopathy.A computer‐aided method proposed in the present work detects and then segments the exudates in the images of retina acquired using a digital fundus camera by (i) gradient method to trace the contour of exudates, (ii) marking the connected candidate pixels to remove false exudates pixels, and (iii) linking the edge pixels for the boundary extraction of exudates.The method is tested on 1307 retinal fundus images with varying characteristics.Six hundred and forty‐nine images were acquired from hospital and the remaining 658 from open‐source benchmark databases, namely, stare, drive messidor, diaret db1, and e‐ophtha.The exudates segmentation method proposed in this research work results in the retinal fundus image‐based (i) accuracy of 98.04%, (ii) sensitivity of 95.345%, and (iii) specificity of 98.63%.The segmentation results for a number of exudates‐based evaluations depict the average (i) accuracy of 95.68%, (ii) sensitivity of 93.44%, and (iii) specificity of 97.22%.The substantial combined performance at image and exudates‐based evaluations proves the contribution of the proposed method in mass screening as well as treatment process of background diabetic retinopathy.

Journal: Journal of Healthcare Engineering (2023)
Publication types: Research Article;
Astragalus Polysaccharides Promote Wound Healing in Diabetic Rats by Upregulating PETN and Inhibiting the mTOR Pathway

Presently, astragalus polysaccharide (aps) is being investigated for its therapeutic potential in various diseases; however, its underlying mechanism has not yet been clarified.This study was aimed at observing the effects of aps on wound healing in diabetic rats and at exploring its underlying mechanism.Methods.Streptozotocin was injected into the tail vein of sd rats to induce diabetic animal models, in which an incision on the back was made.Rats were treated with different dosages of aps to observe their wound healing.Additionally, rt-q pcr and western blot assay were conducted to observe the expression levels of pten and m tor pathway-associated factors.Results.Diabetic rats had a prolonged wound healing process, fewer blood vessels, and increased inflammatory response, in which decreased pten and elevated m tor phosphorylation were also identified.Aps effectively improved wound healing in a dose-dependent manner by inhibiting the release of inflammatory mediators and attenuating endothelial injuries.Suppression of pten could effectively increase the phosphorylation of m tor and diminish the therapeutic functions of aps on wound healing in diabetic rats.Conclusion.This study highlighted that aps could promote wound healing in diabetic rats by upregulating pten and suppressing the m tor pathway activation.

Journal: Computational and Mathematical Methods in Medicine (2022)
Publication types: Research Article;
Association between Perceived Salt Intake and Arterial Stiffness

To explore the association of perceived salt intake (si) level with arterial stiffness in the community population in northern china.We enrolled participants who completed the health questionnaire, physical examination, and brachial‐ankle pulse wave velocity (ba pwv) test during 2010‐2019 and divided them into &lt;6 g (low si), 6‐10 g (medium si), and &gt;10 g (high si) groups based on their daily si.The influence of si on ba pwv was analyzed using the multivariate logistic regression model.A total of 36324 subjects, aged (49.10 ± 12.57) years with a male to female ratio of 25934 : 10390, met the inclusion criteria and were enrolled.The average ba pwv was (1527.73 ± 355.61) cm/s.Logistic regression analysis showed that after adjusting for other confounders, daily si&gt;10 g (high si) was a risk factor for arterial stiffness (ba pwv ≥1400 cm/s), with the odds ratio (95% confidence interval [ci]) of 1.17 (1.04‐1.31).High si is independently associated with arterial stiffness.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Assessment of Saudi Women’s Adherence and Experience with Venous Thromboembolism Prophylaxis after Cesarean Section Delivery Using Telemedicine Technology

Telemedicine technology is widely used especially after the covid-19 pandemic.It can be used to give medical advice as well as follow up with the patients at home in the outpatient setting.Low molecular weight heparin, such as enoxaparin, decreases the risk of venous thromboembolism after cesarean delivery.Objective.Assessing postcesarean women’s adherence and experience to enoxaparin thromboprophylaxis regimens in the outpatient setting via telephone calls.Methods.Prospective cohort study was conducted in the maternity and children hospital (mch).Postcesarean women were interviewed at the postnatal ward in the mch.The participants were followed up for 10 days of the delivery to assess their adherence to and experience with enoxaparin thromboprophylaxis.Suboptimal adherence was defined as the missing of one or more doses of enoxaparin.Results.170 women participated in this study.The majority of them (78.8%) were fully adherent to enoxaparin while 21.2% missed at least one dose.The most-reported causes for suboptimal adherence were perceived lack of necessity (44.4%), forget to take the injection (30.6%), feeling of high load going to the primary care unit to take injection (27.8%), and fear of injection (11.1%).Conclusion.Telemedicine technology could be used to assess patients’ adherence.The study results showed that the majority of participants were fully adherent to postcesarean enoxaparin but more than 20% of the participants were suboptimal adherent.Proper patient education techniques could influence patients’ adherence and potentially decrease the risk of dvt in those populations.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Research Article;
Artificial Neural Network Assisted Cancer Risk Prediction of Oral Precancerous Lesions

The incidence of oral cancer is still increasing.It has become very common in patients with malignant tumors, which has forced medical personnel to continuously explore its treatment methods.What kind of method can effectively and correctly diagnose the disease in the early stage and improve the survival rate has become one of the research topics that have attracted much attention.Aiming at this problem, it has great research significance for the field of oral precancerous lesions diagnosis.With the in‐depth research on oral precancerous diagnosis, the research on artificial neural network (ann) in medical diagnosis is gradually carried out.Its performance advantage is of great significance to solve the problem of early and correct disease diagnosis.This paper aimed to investigate the application of ann‐assisted cancer risk prediction method in risk prediction of oral precancerous lesions.Through the analysis and research of ann and oral cancer, the construction of oral cancer risk prediction model was applied to solve the problem of improving the survival rate of oral cancer patients.In this paper, ann and oral precancerous lesions were analyzed, the performance of the algorithm was experimentally analyzed, and the relevant theoretical formulas were used to explain.The results showed that the method had higher accuracy than traditional forecasting methods.When n = 2, the output accuracy was above 90%.It can be seen that the algorithm can meet the needs of the diagnosis of high‐risk groups of oral cancer lesions, and the diagnosis efficiency and patient survival rate has been greatly improved.

Journal: BioMed Research International (2022)
Publication types: Research Article;
Applications of Healthcare Robots in Combating the COVID-19 Pandemic

Due to the increasing number of covid-19 cases, there is a remarkable demand for robots, especially in the clinical sector.Sars-co v-2 mainly propagates due to close human interactions and contaminated surfaces, and hence, maintaining social distancing has become a mandatory preventive measure.This generates the need to treat patients with minimal doctor-patient interaction.Introducing robots in the healthcare sector protects the frontline healthcare workers from getting exposed to the coronavirus as well as decreases the need for medical personnel as robots can partially take over some medical roles.The aim of this paper is to highlight the emerging role of robotic applications in the healthcare sector and allied areas.To this end, a systematic review was conducted regarding the various robots that have been implemented worldwide during the covid-19 pandemic to attenuate and contain the virus.The results obtained from this study reveal that the implementation of robotics into the healthcare field has a substantial effect in controlling the spread of sars-co v-2, as it blocks coronavirus propagation between patients and healthcare workers, along with other advantages such as disinfection or cleaning.

Journal: Applied Bionics and Biomechanics (2021)
Publication types: Research Article;
Application Value of Management Model Based on “Zero Tolerance” Concept in Pressure Ulcer Management

Pressure injuries are the most prevalent health problem worldwide.Improving the quality of hospital pressure injury management is an important indicator to improve the quality of hospital management.Objective.To explore the application value of the management model centered on the concept of “zero tolerance” in the management of pressure ulcers (pu).Methods.The effects of conventional management mode and management mode centered on the concept of “zero tolerance” on pu patients and nursing staff were retrospectively analyzed.The patients were evaluated by the general comfort questionnaire (gcq), generic quality of life inventory 74 (gqol-74), and pressure ulcer healing scale (push).At the same time, the satisfaction of pu patients and nursing staff with different management modes was investigated.Results.When comparing the conditions of patients under different management modes, it was found that the “zero tolerance” management mode can improve the comfort and quality of life of patients during hospitalization.Compared with the conventional management mode, the “zero tolerance” management mode can significantly improve the degree of pressure ulcer healing in patients.In addition, the “zero tolerance” management model can not only improve the satisfaction of patients with management but also improve the satisfaction of nursing staff with management.Conclusion.Standardized management of pu patients with the concept of “zero tolerance” as the core can improve the health status and quality of life of patients, promote wound healing, and improve the satisfaction of patients and nurses with the management plan.

Journal: Emergency Medicine International (2022)
Publication types: Research Article;
Application Value Analysis of Seven-Autoantibody Panel in the Lung Cancer Screening in Yunnan

To study the application value of seven-autoantibody (anti-cage, anti-gage7, anti-gbu4-5, anti-mage a1, anti-p53, and anti-pgp9.5, anti-sox2) in lung cancer (lc) screening in yunnan.Methods.The clinical data of 329 lung cancer patients and 202 nonlung cancer controls in the first people’s hospital of yunnan province from november 2018 to april 2022 were retrospectively analyzed.The detection results of anti-cage, anti-gage7, anti-gbu4-5, anti-mage a1, anti-p53, anti-pgp9.5, and anti-sox2 were collected.The receiver operating curve (roc) was used to analyze the value of these seven-autoantibody in the detection of lc alone and in combination, and the area under the curve (auc), sensitivity, specificity, and cut-off values were calculated.Results.The levels of anti-cage, anti-gage7, anti-gbu4-5, anti-mage a1, anti-p53, anti-pgp9.5 and anti-sox2 in lc patients were significantly higher than those in the controls, and the differences were statistically significant ( p &lt; 0.001 ).The auc of anti-cage, anti-gage7, anti-gbu4-5, anti-mage a1, anti-p53, anti-pgp9.5, and anti-sox2 for the diagnosis of lc were 0.586 (95% ci: 0.537–0.634, p &lt; 0.001 ), 0.620 (95% ci: 0.572–0.667, p &lt; 0.001 ), 0.570 (95% ci: 0.521–0.619, p = 0.007 ), 0.612 (95% ci: 0.563–0.660, p &lt; 0.007 ) 0.001), 0.561 (95% ci: 0.510–0.611, p = 0.019 ), 0.667 (95% ci: 0.619–0.715, p &lt; 0.001 ), 0.587 (95% ci: 0.538–0.636, p &lt; 0.001 ), respectively.The auc of combined detection of lc was 0.719 (95% ci: 0.676–0.761, p &lt; 0.001 ).The positive rate of the combined detection of seven-autoantibody in the lc group was 48.02% (158/329), which was significantly higher than that of the control group (13.86% (28/202)), the difference was statistically significant (χ2 = 64.183, p &lt; 0.001 ).Conclusion.The individual detection and combined detection of the seven-autoantibody have a certain value in the diagnosis of lc in yunnan, and it can provide a certain reference for clinical lc screening.

Journal: Computational Intelligence and Neuroscience (2022)
Publication types: Research Article;
Application of Wireless Communication Technology in Construction Project Information Management

With the replacement of the times, the electronic information technology of all countries in the world has developed rapidly, and 4g mobile communication technology has also obtained the opportunity of development, which has improved the transmission speed of 5g mobile communication technology, which has been widely used in intelligent information management of construction engineering.Under this background, this paper selects the research methods of theory guiding practice and practice updating theory to guide the application of information technology.Based on the actual engineering cases, this paper discusses the scientific process of information management construction of construction projects from the perspective of bim technology by taking the specific construction details as the starting point.Firstly, this paper systematically introduces the key technologies of bim and the related concepts and basic contents of construction project management informatization, expounds and analyzes the three construction modes that should be followed by construction project collaborative management informatization, and puts forward the key and main contents of standardization construction.Then, taking new york freedom building as an engineering case, this paper analyzes the application of building information modeling (bim) in the architectural design of new york freedom building.Relevant research can provide theoretical and practical references for realizing and ensuring the combination of project management and information technology.

Journal: Wireless Communications and Mobile Computing (2021)
Publication types: Research Article;
Application of Wireless Communication in Experimental Research of the Interface Bonding Condition between Asphalt Layers by Tensile Testing

The vigorous development of communication technology, especially the development of wireless network communication technology, has accelerated its informatization process in more and more industrial applications.In the field of monitoring and detection applications, the many advantages of wireless network transmission technology provide an important reference for high‐quality compaction monitoring.Engineering practice shows that the construction technology of asphalt pavement is the ultimate guarantee of engineering quality.It is important to recognize that pavement performance is greatly influenced by interface bonding condition and interface failure can reduce the serviceability of pavements rather than their overall structural lifetime.This paper presents a laboratory test to investigate the bonding tensile performance between asphalt layers by tensile testing.The test methods and devices for determining the bond regarding tensile testing are summarized as follows.Different interface conditions have been analyzed herein: 0.2, 0.4, and 0.6 kg/m 2 with corresponding emulsified asphalt (ma) and sbs‐modified ma.It is found that the stress‐strain relationship of tensile testing for interface bonding is similar with low‐carbon steels and it can be categorized into four zones.The results of tensile strength and damage displacement are discussed which are key parameters in describing the interface bonding condition and evaluating pavement performance.

Journal: Wireless Communications and Mobile Computing (2021)
Publication types: Research Article;
Application of Wavelet in Quantitative Evaluation of Gait Events of Parkinson’s Disease

Motivation.In parkinson’s disease, disturbances in gait initiation are of particular interest as they affect postural adjustments and movement disorders which may lead to falling.This falling down may be dangerous and at times life threatening, thus becoming a major concern for the patient and the clinician.These gait abnormalities are due to dependencies of movement on the motor system.Paroxysmal dyskinesia (commonly termed as freezing of gait) is one of the extreme cases of motor blocks.Since the last two decades, automated methods for monitoring motor activities, their data analysis, and algorithm techniques have been subjects of research for parkinson’s disease (pd).This research will be of help to clinicians in prescribing a drug regimen.Problem statement.Development of a system based on an algorithm for automatic detection of the freezing of gait (fog) and other postural adjustments, with the help of wearable sensor’s data and to provide a quantitative approach for assessing the intensity of pd by analyzing frequency components associated with different motor movements and gait.Methodology.This paper presents a novel wavelet energy distribution approach to distinguish between walking, standing, and fog.Data from the acceleration sensor is taken as input.After preprocessing, discrete wavelet transform (dwt) is applied on the data which shows its entire frequency spectrum.In the next step, energy is computed for the decomposed level of interest.Results.Systems detected fog and other gait postures and showed time-frequency range by examining differentiated decomposed signals by dwt.Energy distribution and psd graph proved the accuracy of the system.Validation is done by the loso method which shows 90% accuracy for the proposed method.Conclusion.Observations of the clinical trials validate the proposed technique.In comparison to the previous techniques reported in literature, it is seen that the proposed method shows improvement in time and frequency resolution as well as processing time.

Journal: Applied Bionics and Biomechanics (2021)
Publication types: Research Article;
Application of the Whole Optimization of Emergency Nursing Model United and Its Influence on Patients’ Stress Response and Nursing Satisfaction

To investigate the use of an integrated emergency nursing model with a multidisciplinary team (mdt) teaching method for practice of nursing towards multiple trauma in the emergency department and its influence on patients’ stress response and nursing satisfaction.Methods.The research subjects were 120 multiple trauma patients hospitalized to our hospital’s emergency department between january 2019 and january 2020, who were evenly divided into groups a ( n = 60 ) and b ( n = 60 ) based on the sequence of admission.For patients in group a, on the basis of whole optimization of the emergency nursing model, the mdt teaching and training were given to the nursing staff in group a.Patients in group b had their emergency nursing model completely optimized.The assessment scores of nursing staff were compared.The patients’ c-reactive protein (crp) levels in peripheral circulation, first-aid time indices, treatment effect, risk of complications &amp; nursing contentment were all investigated.Results.Nursing personnel in group a had considerably higher achievement scores than staff nurses in group b ( p &lt; 0.001 ).Crp levels in group a were considerably lower following therapy ( p &lt; 0.05 ) than those in group b.The time it took for group a to receive first assistance was considerably less than that for group b ( p &lt; 0.001 ).Group a had a considerably superior treatment effect than group b ( p &lt; 0.05 ).Complications occurred at a lower rate in group a ( p &lt; 0.05 ) than in group b.Group a nurses were more satisfied than group b nurses ( p &lt; 0.05 ).Conclusion.The entire optimization of the emergency nursing model combined with the mdt way of teaching can abbreviate the rescue process, reduce stress, improve treatment effect &amp; reduce the possibility of complications in multiple trauma patients in the emergency department, and patients seem to be more comfortable with this nursing model.As a result, it should become more well known.

Journal: Applied Bionics and Biomechanics (2022)
Publication types: Clinical Study;