Cloud-based Electronic Health Records (EHRs) have seen a substantial increase in usage in recent years, especially for remote patient monitoring. Researchers are interested in investigating the use of Healthcare 4.0 in smart cities. This involves using Internet of Things (IoT) devices and cloud computing to remotely access medical processes. Healthcare 4.0 focuses on the systematic gathering, merging, transmission, sharing, and retention of medical information at regular intervals. Protecting the confidential and private information of patients presents several challenges in terms of thwarting illegal intrusion by hackers. Therefore, it is essential to prioritize the protection of patient medical data that is stored, accessed, and shared on the cloud to avoid unauthorized access or compromise by the authorized components of E-healthcare systems. A multitude of cryptographic methodologies have been devised to offer safe storage, exchange, and access to medical data in cloud service provider (CSP) environments. Traditional methods have not been effective in providing a harmonious integration of the essential components for EHR security solutions, such as efficient computing, verification on the service side, verification on the user side, independence from a trusted third party, and strong security. Recently, there has been a lot of interest in security solutions that are based on blockchain technology. These solutions are highly effective in safeguarding data storage and exchange while using little computational resources. The researchers focused their efforts exclusively on blockchain technology, namely on Bitcoin. The present emphasis has been on the secure management of healthcare records through the utilization of blockchain technology. This study offers a thorough examination of modern blockchain-based methods for protecting medical data, regardless of whether cloud computing is utilized or not. This study utilizes and evaluates several strategies that make use of blockchain. The study presents a comprehensive analysis of research gaps, issues, and a future roadmap that contributes to the progress of new Healthcare 4.0 technologies, as demonstrated by research investigations.
Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B
... Show MoreCorrelation equations for expressing the boiling temperature as direct function of liquid composition have been tested successfully and applied for predicting azeotropic behavior of multicomponent mixtures and the kind of azeotrope (minimum, maximum and saddle type) using modified correlation of Gibbs-Konovalov theorem. Also, the binary and ternary azeotropic point have been detected experimentally using graphical determination on the basis of experimental binary and ternary vapor-liquid equilibrium data.
In this study, isobaric vapor-liquid equilibrium for two ternary systems: “1-Propanol – Hexane – Benzene” and its binaries “1-Propanol –
... Show MoreIn this study, we made a comparison between LASSO & SCAD methods, which are two special methods for dealing with models in partial quantile regression. (Nadaraya & Watson Kernel) was used to estimate the non-parametric part ;in addition, the rule of thumb method was used to estimate the smoothing bandwidth (h). Penalty methods proved to be efficient in estimating the regression coefficients, but the SCAD method according to the mean squared error criterion (MSE) was the best after estimating the missing data using the mean imputation method
A two time step stochastic multi-variables multi-sites hydrological data forecasting model was developed and verified using a case study. The philosophy of this model is to use the cross-variables correlations, cross-sites correlations and the two steps time lag correlations simultaneously, for estimating the parameters of the model which then are modified using the mutation process of the genetic algorithm optimization model. The objective function that to be minimized is the Akiake test value. The case study is of four variables and three sites. The variables are the monthly air temperature, humidity, precipitation, and evaporation; the sites are Sulaimania, Chwarta, and Penjwin, which are located north Iraq. The model performance was
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
... Show MoreThese days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that. The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce
... Show MoreMany financial institutions invest their surplus funds in stocks, either to obtain dividends or for trading purposes and to obtain profits from the difference between the cost and the selling price, and investment in shares represents an important part of the financial position of financial institutions applying to the common accounting system of banks and insurance companies, in addition to their impact It is clear on the result of the activity of these institutions.The aim of the research is to define what the shares and their types are, and to indicate the accounting treatments needed to move towards the process of adopting the International Financial Reporting Standard No. (9) and its reflection on its financial statements. I
... Show MoreAn anal fissure which does not heal with conservative measures as sits baths and laxatives is a chronic anal fissure. Physiologically, it is the high resting tone of the internal anal sphincter that chiefly interferes with the healing process of these fissures. Until now, the gold standard treatment modality is surgery, either digital anal dilatation or lateral sphincterotomy. However, concerns have been raised about the incidence of faecal incontinence after surgery. Therefore, pharmacological means to treat chronic anal fissures have been explored.A Medline and pub med database search from 1986-2012 was conducted to perform a literature search for articles relating to the non-surgical treatment of chronic anal fissure.Pharmacological s
... Show MoreAn anal fissure which does not heal with conservative measures as sits baths and laxatives is a chronic anal fissure. Physiologically, it is the high resting tone of the internal anal sphincter that chiefly interferes with the healing process of these fissures. Until now, the gold standard treatment modality is surgery, either digital anal dilatation or lateral sphincterotomy. However, concerns have been raised about the incidence of faecal incontinence after surgery. Therefore, pharmacological means to treat chronic anal fissures have been explored.A Medline and pub med database search from 1986-2012 was conducted to perform a literature search for articles relating to the non-surgical treatment of chronic anal fissure.Pharmacological s
... Show MoreMedical image segmentation is one of the most actively studied fields in the past few decades, as the development of modern imaging modalities such as magnetic resonance imaging (MRI) and computed tomography (CT), physicians and technicians nowadays have to process the increasing number and size of medical images. Therefore, efficient and accurate computational segmentation algorithms become necessary to extract the desired information from these large data sets. Moreover, sophisticated segmentation algorithms can help the physicians delineate better the anatomical structures presented in the input images, enhance the accuracy of medical diagnosis and facilitate the best treatment planning. Many of the proposed algorithms could perform w
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