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Visual Analytics for Electronic Health Records: A Review
The increasing use of electronic health record (EHR)-based systems has led to the generation of clinical data at an unprecedented rate, which produces an untapped resource for healthcare experts to improve the quality of care. Despite the growing demand for adopting EHRs, the large amount of clinical data has made some analytical and cognitive processes more challenging. The emergence of a type of computational system called visual analytics has the potential to handle information overload challenges in EHRs by integrating analytics techniques with interactive visualizations. In recent years, several EHR-based visual analytics systems have been developed to fulfill healthcare experts’ computational and cognitive demands. In this paper, we conduct a systematic literature review to present the research papers that describe the design of EHR-based visual analytics systems and provide a brief overview of 22 systems that met the selection criteria. We identify and explain the key dimensions of the EHR-based visual analytics design space, including visual analytics tasks, analytics, visualizations, and interactions. We evaluate the systems using the selected dimensions and identify the gaps and areas with little prior work.
Journal Article
Recent progress and trends in predictive visual analytics
A wide variety of predictive analytics techniques have been developed in statistics, machine learning and data mining; however, many of these algorithms take a black-box approach in which data is input and future predictions are output with no insight into what goes on during the process. Unfortunately, such a closed system approach often leaves little room for injecting domain expertise and can result in frustration from analysts when results seem spurious or confusing. In order to allow for more human-centric approaches, the visualization community has begun developing methods to enable users to incorporate expert knowledge into the prediction process at all stages, including data cleaning, feature selection, model building and model validation. This paper surveys current progress and trends in predictive visual analytics, identifies the common framework in which predictive visual analytics systems operate, and develops a summarization of the predictive analytics workflow.
Journal Article
Data visualization : a practical introduction
\"This book provides students and researchers a hands-on introduction to the principles and practice of data visualization. It explains what makes some graphs succeed while others fail, how to make high-quality figures from data using powerful and reproducible methods, and how to think about data visualization in an honest and effective way. Data visualization builds the reader's expertise in ggplot2, a versatile visualization library for the R programming language ....\"--Page 4 of cover.
Book
SynCoPa: Visualizing Connectivity Paths and Synapses Over Detailed Morphologies
Brain complexity has traditionally fomented the division of neuroscience into somehow separated compartments; the coexistence of the anatomical, physiological, and connectomics points of view is just a paradigmatic example of this situation. However, there are times when it is important to combine some of these standpoints for getting a global picture, like for fully analyzing the morphological and topological features of a specific neuronal circuit. Within this framework, this article presents SynCoPa, a tool designed for bridging gaps among representations by providing techniques that allow combining detailed morphological neuron representations with the visualization of neuron interconnections at the synapse level. SynCoPa has been conceived for the interactive exploration and analysis of the connectivity elements and paths of simple to medium complexity neuronal circuits at the connectome level. This has been done by providing visual metaphors for synapses and interconnection paths, in combination with the representation of detailed neuron morphologies. SynCoPa could be helpful, for example, for establishing or confirming a hypothesis about the spatial distributions of synapses, or for answering questions about the way neurons establish connections or the relationships between connectivity and morphological features. Last, SynCoPa is easily extendable to include functional data provided, for example, by any of the morphologically-detailed simulators available nowadays, such as Neuron and Arbor, for providing a deep insight into the circuits features prior to simulating it, in particular any analysis where it is important to combine morphology, network topology, and physiology.
Journal Article
It’s All Analytics
Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, analytics, is an overarching description of a compilation of methodologies. But, AI (artificial intelligence), statistics, decision science, and , optimization, which, have been around for decades, have resurged. Also, things like business intelligence, on-line analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and, terminology?
This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.
eBook
User-centered evaluation of visual analytics
\"Visual analytics has come a long way since its inception in 2005. The amount of data in the world today has increased significantly and experts in many domains are struggling to make sense of their data. This book describes the efforts that go into analysis, including critical thinking, sensemaking, and various analytics techniques learned from the intelligence community. Support for these components is needed in order to provide the most utility for the expert users\"--Page 4 of cover.
Book
Learn Tableau by working on exciting dashboards
Learn how to bring your data to life with this hands-on guide to Tableau. About This Video: Understand Tableau fundamentals such as dimensions, measures, fields (discrete and continuous), aggregation, granularity, and filters. Learn how to explore, analyze, and present data to provide business insights. Learn to create sales analysis, Netflix analysis, and investment portfolio analysis. In Detail: This comprehensive Tableau course is designed to take you from beginner to intermediate in creating stunning and impactful dashboards. Whether you are new to Tableau or have some prior experience, this course covers all the necessary steps to enhance your skills. Starting from the basics, you will learn about Tableau’s installation process and gain a solid foundation in its key features. Throughout the course, you will explore various visualization techniques and tools that Tableau offers, including donut charts, KPI cards, waterfall charts, dual-axis charts, and more. You will also discover advanced concepts such as level of detail expressions and quick table calculations, enabling you to create intricate and insightful visualizations. Hands-on practice is a crucial component of this course, and you will have the opportunity to create four different dashboards and views. These practical exercises include building a sales analysis dashboard, analyzing Netflix data, managing an investment portfolio dashboard, and identifying the top 10 books. Through these real-world examples, you will gain practical experience and confidence in creating your own customized dashboards. By the end of this course, you will have the expertise and knowledge to create professional dashboards in Tableau for various projects and requirements.
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