Anticipation of Living Status of Hepatitis B Patient by using Machine Learning

Recently the methods of Data mining and machine learning are widely used in medical field. These methods/techniques have given better results in the prediction of respective diseases. Hepatitis B is a Liver inflammation; it can affect people of all age groups. Lakhs of people across the globe are thought to be affected by Hepatitis B. Early prediction of Hepatitis B with accurate results can save many people. Hepatitis B is a tough challenge for public health care system because of limited clinical diagnosis in the early stages of disease. This paper presents the decision tree algorithm to diagnose the Hepatitis B. The proposed algorithm includes collection of datasets, pre-processing, EDA (Exploratory Data Analysis), Feature Selection, data visualizing, Interpreting, saving and evaluating the model. After the data visualization process decision tree algorithm is implemented to diagnose the disease along with the patient chances of living. Keywords: Hepatitis B virus, Machine Learning, Decision Tree, Public Health, EDA

Power Business Intelligence in the Data Science Visualization Process to Forecast CPO Prices

Forecasting is one of the techniques in data mining by utilizing the data available in the data warehouse. With the development of science, forecasting techniques have also entered the computational field where the forecasting technique uses the artificial neural network (ANN) method. Where is the method for simple forecasting using the Time Series method. However, the ability to create data visualizations certainly hinders researchers from maximizing research results. Of course, with the development of the Power BI software, the data science process is more neatly presented in the form of visualization, where the data science process involves various fields so that in this paper the results of forecasting the price of crude palm oil (CPO) are presented for the development of the CPO business with the hope of implementing the Business Process. intelligence (BI) by involving ANN, namely the time series for forecasting. From the final results, accuracy in forecasting with time series involves 2 accuracy techniques, the first using MAPE and getting a result of 0.03214% and the second using MSE to get 962.91 results.

Correction: Chen et al. Mechanisms of Azole Resistance and Trailing in Candida tropicalis Bloodstream Isolates. J. Fungi 2021, 7, 612

Because the geometric means of fluconazole and voriconazole in some isolates were not correctly input into the low trailing or high trailing WT group during the visualization process when using GraphPad Prism [...]

Isolation of Metallothionein (MT) Gene from Phytoremediation Agent, Eleusine indica

Belulang grass (Eleusine indica) is a plant in the Poaceae family that is commonly found in the coastal area of Dumai, Riau Province. Eleusine indica is characterized by narrow leaves, concave stems that can reach up to 95 cm high and strong roots. E. indica is known to be very tolerant of its environment, including the environment contaminated with heavy metals. The ability of E. indica as a phytoremediation agent in absorbing heavy metals has been widely known as the role of metallothionein (MT) protein. MT is believed to have a function in the metal metabolism and detoxification process through the metal chelating interaction between the cysteine amino acid residues. This unique function prompted the interest to isolate the MT gene from E. indica. This method involves the isolation of genomic DNA from E. indica followed by the process of amplification of the MT gene using specific primers, namely MTFS and MTRS by polymerase chain reaction (PCR) technology. The success of the MT gene isolation process from E. indica was evidenced by the presence of a single band size of around 172 bp via the visualization process on 1% agarose gel. Furthermore, the results of the PCR product are purified for the purpose of sequencing activity. The results of sequencing analysis of the 172 bp fragment showed 99.31% identical similarity with the complete metallothionein gene from E. indica (DQ082855.1) by using the BLASTN tool, NCBI website.

An Overview of Ontologies in Virtual Reality-Based Training for Healthcare Domain

Virtual reality (VR) is one of the state-of-the-art technological applications in the healthcare domain. One major aspect of VR applications in this domain includes virtual reality-based training (VRT), which simplifies the complicated visualization process of diagnosis, treatment, disease analysis, and prevention. However, not much is known on how well the domain knowledge is shared and considered in the development of VRT applications. A pertinent mechanism, known as ontology, has acted as an enabler toward making the domain knowledge more explicit. Hence, this paper presents an overview to reveal the basic concepts and explores the extent to which ontologies are used in VRT development for medical education and training in the healthcare domain. From this overview, a base of knowledge for VRT development is proposed to initiate a comprehensive strategy in creating an effective ontology design for VRT applications in the healthcare domain.

Building Information Modeling Methods for Post-Earthquake Retrofitting Visualization of Buildings Using Augmented Reality

The post-earthquake retrofitting and repair process of a building is a key factor in improving its seismic capability. A thorough understanding of retrofitting methods and processes will aid in repairing post-earthquake buildings and improving seismic resilience. This study aims to develop a visualization framework for the post-earthquake retrofitting of buildings which builds models based on building information modeling (BIM) and realizes visualization using augmented reality (AR). First, multi-level representation methods and coding criteria are used to process the models for a damaged member. Then, an information collection template is designed for integrating multi-dimensional information, such as damage information, retrofitting methods, technical solutions, and construction measures. Subsequently, a BIM model is presented in three dimensions (3D) using AR. Finally, the visualization process is tested through experiments, which demonstrate the feasibility of using the framework to visualize the post-earthquake retrofitting of a building.

Interpreting Information Visualization

Information visualization has become a prevailing part of our visual culture, a research field, and a line of work for designers. The literature on information visualization is diverse, dominated by handbooks aimed at designers and illustrated surveys, sometimes with an emphasis on historical examples. This chapter makes a survey of the field of information visualization in order to map out and assess its analytical vocabulary. First, there is a need to refer to some different definitions and general concepts, such as the naming of phases in the visualization process, the naming of different visualization types, and their components. In order for scholars of human sciences to be able to identify, understand, and interpret information visualization as visual objects, some tools for suitable visual analysis of these objects would be useful. To meet this end, the chapter explores two particular interpretative frameworks. The first framework discusses social semiotics as an analytical tool. The second one analyzes the ethics and emotional appeal of information visualization.

Improving the Decision-Making Process in a Hospital Environment With New Interactive Visualization Methods

A large number of medical errors occurring in hospitals happen in the diagnostic process, such as the use of outmoded tests and the failure to perform on test results, leading to delays in the diagnosis. Thus, fast and efficient access to the patients' exams and test results is essential to provide them adequate treatment. This need demands solving problems that exist during this process of consulting the results in order to reduce clinical risk. Therefore, an analysis of the problems in the visualization process of the exams in Centro Hospitalar do Porto was carried out, leading to the development of a new platform - AIDA-MCDT, whose main objective was to fill the gaps verified, making the access to exams' results more efficient and intuitive. This platform has significantly improved the system's usability, including several features designed to help healthcare professionals make decisions more quickly and securely.

Visual Comparator: An Interactive Tool for Dynamic Spatiotemporal Comparative Visualizations

Visualizations enable us to detect patterns, time-evolving features, and trends in complex datasets that might not be obvious by looking at the raw data. The visual exploration process often requires comparisons between multiple visualizations, either from the same dataset or a different one, to identify relationships and patterns. This visualization process, referred to as comparative visualization, is valuable for analyzing multivariate, multispectral, or multidimensional data. The existing tools that facilitate visual comparisons do this by three means: juxtaposition (placing visuals side by side), superposition (overlaying visuals), and explicit encoding (visualizing a derived quantity corresponding to the relationship being studied). While superposition is ideal for static, geospatial datasets, where spatialization is a key component of the data, the spatiotemporal nature of Earth science datasets presents a challenge with comparative visualizations. Visual Comparator is an interactive, cross-platform (desktops, kiosks, and web), open-source application, developed to address this shortcoming. The application is used to superimpose and compare up to three synchronized, animated visualizations, and a transition between the visualizations is provided through a slider-based interface. This form of visualization has the advantage of drawing the viewers’ attention to changes between the datasets, enabling comparisons of scale, and reducing the clutter caused by having multiple variables in one visual. This article provides an overview of the project, a brief review of literature pertaining to human perception research and comparative visualizations, and a guide to accessing this application.