Modeling user preference dynamics with coupled tensor factorization for social media recommendation

An essential problem in real-world recommender systems is that user preferences are not static and users are likely to change their preferences over time. Recent studies have shown that the modelling and capturing the dynamics of user preferences lead to significant improvements on recommendation accuracy and, consequently, user satisfaction. In this paper, we develop a framework to capture user preference dynamics in a personalized manner based on the fact that changes in user preferences can vary individually. We also consider the plausible assumption that older user activities should have less influence on a user’s current preferences. We introduce an individual time decay factor for each user according to the rate of his preference dynamics to weigh the past user preferences and decrease their importance gradually. We exploit users’ demographics as well as the extracted similarities among users over time, aiming to enhance the prior knowledge about user preference dynamics, in addition to the past weighted user preferences in a developed coupled tensor factorization technique to provide top-K recommendations. The experimental results on the two real social media datasets—Last.fm and Movielens—indicate that our proposed model is better and more robust than other competitive methods in terms of recommendation accuracy and is more capable of coping with problems such as cold-start and data sparsity

TSCMF: Temporal and social collective matrix factorization model for recommender systems

In real-world recommender systems, user preferences are dynamic and typically change over time. Capturing the temporal dynamics of user preferences is essential to design an efficient personalized recommender system and has recently attracted significant attention. In this paper, we consider user preferences change individually over time. Moreover, based on the intuition that social influence can affect the users’ preferences in a recommender system, we propose a Temporal and Social CollectiveMatrix Factorization model called TSCMF for recommendation.We jointly factorize the users’ rating information and social trust information in a collective matrix factorization framework by introducing a joint objective function. We model user dynamics into this framework by learning a transition matrix of user preferences between two successive time periods for each individual user. We present an efficient optimization algorithm based on stochastic gradient descent for solving the objective function. The experiments on a real-world dataset illustrate that the proposed model outperforms the competitive methods.Moreover, the complexity analysis demonstrates that the proposed model can be scaled up to large datasets

Hypertension Prediction in Primary School Students Using an Ensemble Machine Learning Method

Introduction: The prevalence of hypertension in children is increasing, and this complication is considered the most important risk factor for cardiovascular diseases in older age. Early detection and control of hypertension can prevent its progress and reduce its consequences. Machine learning methods can help predict this complication promptly and reduce cost and time. This study aimed to provide a model based on ensemble machine learning methods to more accurately predict the hypertension of primary school children. Method: This is an applied developmental study that was conducted using the information of 1287 primary school children aged 7-13 years in Kashmar city. After data preprocessing, to achieve a more accurate diagnosis of hypertension in children, the output results of five common machine learning methods in disease diagnosis including decision tree, naive Bayesian, nearest neighbors, artificial neural network, and support vector machine using weighted majority voting method were combined. Results: The results showed that the accuracy, sensitivity, and specificity of the proposed model were 90.31%, 80.65%, and 93.54%, respectively, and compared to similar studies it performed better. Conclusion: The proposed model can better predict and diagnose hypertension in children and improve accuracy and reduce the error rate. This model can be a useful and early tool in the diagnosis of hypertension in children, reducing the consequences and costs of this complication and being a big step in the fight against hypertension

Review of Unusual Presentations of COVID-19

The world has faced the coronavirus disease 2019 (COVID-19) pandemic since the H1N1 influenza pandemic in 1918. The symptoms of this disease are spreading rapidly and affect almost all systems of the body. In addition to the common symptoms of the virus, numerous reports of rare symptoms of the virus have also been published. These atypical presentations can result in difficulty in diagnosing the disease. The aim of this work is to summarize “uncommon atypical presentations”, which have not received enough attention in descriptions of the disease presentation to date and the authors specifically discuss the important uncommon atypical presentations of COVID-19

Evaluation of the modified HTK solution in pancreas transplantationdAn experimental model

One of the great challenges in pancreas transplantation is the ischemia reperfusion injury. It is mentioned that free oxygen and/or nitrogen radicals play a prominent role in this phase. To minimize this problem, a modified histidineetryptophan eketoglutarate (HTK) solution that contains modified antioxidants has been developed. Our aim was to evaluate this solution in improving the viability of the pancreas in comparison with standard HTK and University of Wisconsin (UW) solutions in a porcine model of pancreas transplantation

Replacement of Missing Values and its Effect on the Classification Accuracy in Medical Data Mining

Introduction: The missing values in medical data may impact the data mining process and any kind of interpretation. Thus the treatment of these missing values is a necessary task. In this research, the effect of various methods of dealing with missing values on medical data classification accuracy is evaluated. Method: This paper studied the effect of missing data replacement methods including Mean/Mode, Hot Deck, K-Nearest Neighbor, Maximum Possible Value, All Possible Value, Case Deletion, and Regression on classification accuracy for two popular classifiers namely K-nearest-neighbor and Neural Networks from Weka Data mining tool on 10 medical datasets including Breast Cancer, Cardiac Problems, Dermatology, Hepatitis, Thyroid, Diabetes, Primary Tumor, Liver Patient, Lung Cancer and Post-Operative Patient. These were selected from the six amounts of missing values. For classification accuracy estimation, the 10-fold cross validation method is used. Results: The results show that although the mean/mode method almost had better classification improvement that, none of the replacement methods for all amounts of missing values, is not always the most accurate classification with increasing amounts of missing values for the K-nearest-neighbor classifier. There was no supremacy for all the replacement methods against the various amounts of missing values for any of the replacement methods for all data sets with different amounts of missing values. Conclusion: The current study shows that the replacement methods that have been evaluated for all the different rates of missing values do not necessarily improve the accuracy of classification and none of the investigated replacement methods is not absolutely the best one

Influence of a modified preservation solution in kidney transplantation: A comparative experimental study in a porcine model

Currently, due to lack of optimal donors, more marginal organs are transplanted. Therefore, there is a high interest to ameliorate preischemic organ preservation, especially for critical donor organs. In this regard, a new histidinetryptophane ketoglutarate (HTK-N) solution has been designed and its protective efficacy was compared with the standard preservation solutionsdUniversity of Wisconsin solution and standard HTK or Custodiol (Bretschneider’s solution). Methods: Seventy-two landrace pigs were included into the study, as donors and recipients. The donor kidneys were perfused during explantation with cold University of Wisconsin solution (n Z 12), standard HTK (n Z 12), or HTK-N solutions (n Z 12), kept in the respective preservation solution at 4 C for 30 hours, implanted in the recipient pigs, and reperfused. The pigs survived in daily control for 7 days. The serum creatinine and blood urea nitrogen were assessed in pre- and postreperfusion phase on the 3rd day and 7th day posttransplantation. Additionally, tissue samples were taken to analyze the histopathological degree of tubular injury and regeneration before and after reperfusion

Influence of a modified preservation solution in kidney transplantation: A comparative experimental study in a porcine model

Background/Objective: Currently, due to lack of optimal donors, more marginal organs are transplanted. Therefore, there is a high interest to ameliorate preischemic organ preservation, especially for critical donor organs. In this regard, a new histidine-tryptophane ketoglutarate (HTK-N) solution has been designed and its protective efficacy was compared with the standard preservation solutions—University of Wisconsin solution and standard HTK or Custodiol (Bretschneider's solution). Methods: Seventy-two landrace pigs were included into the study, as donors and recipients. The donor kidneys were perfused during explantation with cold University of Wisconsin solution (n = 12), standard HTK (n = 12), or HTK-N solutions (n = 12), kept in the respective preservation solution at 4°C for 30 hours, implanted in the recipient pigs, and reperfused. The pigs survived in daily control for 7 days. The serum creatinine and blood urea nitrogen were assessed in pre- and postreperfusion phase on the 3rd day and 7th day posttransplantation. Additionally, tissue samples were taken to analyze the histopathological degree of tubular injury and regeneration before and after reperfusion. Results: The three preservation groups were comparable in age, body weight, and hemodynamic parameters. According to statistical proof, they differed in none of the control parameters. Conclusion: Although the new preservation HTK solution is in several points a well-thought-out modification of the standard HTK solution, its preservation efficacy, at least for kidney preservation in a pig model for 30 hours, seems to be comparable to the current used solutions. A real advantage, however, could be confirmed in clinical settings, where marginal organs may influence the clinical outcome

Influence of a modified preservation solution in kidney transplantation: A comparative experimental study in a porcine model

Currently, due to lack of optimal donors, more marginal organs are transplanted. Therefore, there is a high interest to ameliorate preischemic organ preservation, especially for critical donor organs. In this regard, a new histidine-tryptophane ketoglutarate (HTK-N) solution has been designed and its protective efficacy was compared with the standard preservation solutions—University of Wisconsin solution and standard HTK or Custodiol (Bretschneiders solution). Seventy-two landrace pigs were included into the study, as donors and recipients. The donor kidneys were perfused during explantation with cold University of Wisconsin solution (n = 12), standard HTK (n = 12), or HTK-N solutions (n = 12), kept in the respective preservation solution at 4°C for 30 hours, implanted in the recipient pigs, and reperfused. The pigs survived in daily control for 7 days. The serum creatinine and blood urea nitrogen were assessed in pre- and postreperfusion phase on the 3rd day and 7th day posttransplantation. Additionally, tissue samples were taken to analyze the histopathological degree of tubular injury and regeneration before and after reperfusion. The three preservation groups were comparable in age, body weight, and hemodynamic parameters. According to statistical proof, they differed in none of the control parameters. Although the new preservation HTK solution is in several points a well-thought-out modification of the standard HTK solution, its preservation efficacy, at least for kidney preservation in a pig model for 30 hours, seems to be comparable to the current used solutions. A real advantage, however, could be confirmed in clinical settings, where marginal organs may influence the clinical outcome

Evaluation of the modified HTK solution in pancreas transplantation—An experimental model

One of the great challenges in pancreas transplantation is the ischemia reperfusion injury. It is mentioned that free oxygen and/or nitrogen radicals play a prominent role in this phase. To minimize this problem, a modified histidine–tryptophan–ketoglutarate (HTK) solution that contains modified antioxidants has been developed. Our aim was to evaluate this solution in improving the viability of the pancreas in comparison with standard HTK and University of Wisconsin (UW) solutions in a porcine model of pancreas transplantation. Twenty-three Landrace pigs were divided into three identical groups. After a 10-hour preservation time at 4°C, the pancreas was implanted in the organs of the recipients in a standardized manner. Serum parameters were assessed prior to and after implantation on the 1st postoperative day, 3rd postoperative day, and 7th postoperative day. Furthermore, three biopsies were taken: prior to and after reperfusion, and on Day 7 to assess the grafts. An analysis of serum glucose among the three groups showed no significant differences. Evaluation of the insulin levels showed no significant difference between the modified and standard HTK groups, however, differences between HTK and UW were significant (p = 0.004 in favor of UW solutions). The histopathological results showed a trend of a higher grade of rejection of pancreas tissue in the UW group compared to both HTK groups. The modified HTK solution could preserve the pancreas for the preservation of the graft with similar results to those observed for standard solutions without any significant difference. The trend showed that the pathological finding in the UW group was not as good as that in the modified HTK and standard HTK groups