Products related to Care:
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Conceptual Care Mapping : Case Studies for Improving Communication, Collaboration, and Care
Learn to prioritize patient care quickly and effectively!Conceptual Care Mapping: Case Studies for Improving Communication, Collaboration, and Care uses a 'two books in one' approach to guide you through the most important aspects of patient care and critical thinking.The first section explores the title's three C's of care, communication, and collaboration within the healthcare team.The second section includes case studies that progress from simple clinical conditions to the more complex.Conceptual Care Mapping provides the tools you need to understand and implement effective patient care plans.With mapping practice both online and in the text, this unique book is the ideal resource for any first-year nursing student!Unique! Conceptual Care Mapping guides your care - using templates and an online, interactive conceptual care map creator - from the author team who developed this new method of organizing care information. Unique! 30 case studies focus on the patients you are most likely to see in clinical experience as a first-year student - and are organized from simple to complex, guiding you through prioritization and teaching you to think critically. Unique! Elsevier's Conceptual Care Map (CCM) creator helps you create, update, manage, and submit care maps quickly and effectively. Unique! Answers and completed care maps are provided for selected cases to reinforce what you've learned. Unique! Improving Patient Care section not only provides an overview of care mapping, but also focuses on three key elements of patient care: care, communication (both with other healthcare professionals and with patients), and collaboration. Unique! Interprofessional Education (IPE) and collaboration are key elements in all of the case studies, helping you understand how you will work within the larger healthcare team. Full-color design makes it easier to match up your online care mapping with content in the text.
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Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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Bioinformatics Tools and Big Data Analytics for Patient Care
Nowadays, raw biological data can be easily stored as databases in computers but extracting the required information is the real challenge for researchers.For this reason, bioinformatics tools perform a vital role in extracting and analyzing information from databases.Bioinformatics Tools and Big Data Analytics for Patient describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery for patient care.The book gives details about the recent developments in the fields of artificial intelligence, cloud computing, and data analytics.It highlights the advances in computational techniques used to perform intelligent medical tasks. Features:Presents recent developments in the fields of artificial intelligence, cloud computing, and data analytics for improved patient care. Describes the applications of bioinformatics, data management, and computational techniques in clinical studies and drug discovery. Summarizes several strategies, analyses, and optimization methods for patient healthcare. Focuses on drug discovery and development by cloud computing and data-driven researchThe targeted audience comprises academics, research scholars, healthcare professionals, hospital managers, pharmaceutical chemists, the biomedical industry, software engineers, and IT professionals.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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Is spatial visualization important for engineers?
Yes, spatial visualization is important for engineers as it allows them to mentally manipulate and understand complex 3D objects and structures. Engineers often need to design and analyze various components and systems, and spatial visualization skills help them to conceptualize and communicate their ideas effectively. Whether it's designing a new product, creating blueprints for a building, or solving complex problems, spatial visualization is a crucial skill that allows engineers to think critically and innovate in their field.
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Can one improve their spatial visualization skills?
Yes, it is possible to improve spatial visualization skills through practice and training. Engaging in activities such as puzzles, building models, and playing spatial reasoning games can help develop these skills. Additionally, practicing mental rotation exercises and regularly challenging oneself with spatial tasks can also contribute to improvement. With consistent effort and dedication, individuals can enhance their spatial visualization abilities over time.
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What are problems with spatial visualization skills?
Some problems with spatial visualization skills include difficulty in understanding and interpreting maps, graphs, and diagrams. Individuals with poor spatial visualization skills may struggle with tasks such as navigating through unfamiliar environments, understanding 3D objects, and mentally rotating objects. This can impact their performance in subjects such as math, science, and engineering, as well as in everyday activities such as driving and assembling furniture. Additionally, poor spatial visualization skills can lead to frustration and decreased confidence in one's abilities.
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Spatial Epidemiological Approaches in Disease Mapping and Analysis
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.
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Crime Mapping and Spatial Data Analysis using R
Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
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Big Data Analytics and Intelligence : A Perspective for Health Care
Big data is a field of research that is growing rapidly, and as the Covid-19 crisis has shown, health care is an area that could benefit greatly from its increased use and application.Big data, as derived partly from the internet of things and analysed according to specific algorithms, has a large and beneficial role to play in preventative medicine, in monitoring the health of specific groups, and in improving diagnostics. Big Data Analytics and Intelligence: A Perspective for Health Care focuses on various areas of health care, ranging from nutrition to cancer, and providing diverse perspectives on all of them.This book explores the entire life-cycle of big data, from information retrieval to analysis, and it shows how big data’s applications can enhance, streamline and improve services for patients and health-care professionals.Each chapter focuses on a specific area of health care and how big data is applicable to it, with background and current examples provided.
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An Introduction to R for Spatial Analysis and Mapping
The ever-expanding availability of spatial data continues to revolutionise research.This book is your go-to guide to getting the most out of handling, mapping and analysing location-based data. Without assuming prior knowledge of GIS, geocomputation or R, this book helps you understand spatial analysis and mapping and develop your programming skills, from learning about scripting and writing functions to point pattern analysis and spatial attribute analysis. The book:Illustrates approaches to analysis on a range of datasets that are new to this edition. Enables you to put your skills into practice with embedded exercises and over 30 self-test questions. Showcases the possibilities of using spatial analysis to explore spatial inequalities. Whether you’re an R novice or experienced user, this book equips upper undergraduates, postgraduates and researchers with the tools needed for spatial data handling and rich analysis.
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What is the function of spatial visualization ability?
Spatial visualization ability allows individuals to mentally manipulate and understand spatial relationships between objects. This ability is crucial in fields such as engineering, architecture, and design, where individuals need to visualize and manipulate complex 3D objects and structures. It also plays a key role in tasks such as navigation, map reading, and understanding geometric concepts. Overall, spatial visualization ability is important for problem-solving, creativity, and understanding the physical world.
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What does it mean if someone lacks spatial visualization skills?
If someone lacks spatial visualization skills, it means that they have difficulty mentally manipulating and understanding spatial relationships between objects and shapes. This can manifest as challenges in tasks such as reading maps, understanding 3D objects, or visualizing how objects fit together in space. People with this difficulty may struggle with activities such as assembling furniture, reading graphs, or understanding geometric concepts. It's important to note that lacking spatial visualization skills does not indicate a lack of intelligence, but rather a specific cognitive challenge in this area.
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Is social care better than elderly care?
It is not accurate to say that one type of care is better than the other as both social care and elderly care serve different purposes and cater to different needs. Social care focuses on providing support and assistance to individuals of all ages who may be vulnerable or in need of help, while elderly care specifically targets the unique needs of older adults. The effectiveness of each type of care depends on the individual's specific circumstances and requirements. Ultimately, the most important factor is ensuring that individuals receive the appropriate care and support that meets their needs and enhances their quality of life.
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Should I not care or should I care?
Whether you should care or not depends on the situation and the impact it has on you or others. It's important to prioritize your mental and emotional well-being, so if something is causing you unnecessary stress or harm, it may be better to let it go. However, caring about important issues, relationships, and personal growth can lead to positive outcomes and fulfillment. Ultimately, finding a balance between caring for yourself and others while also setting boundaries is key.
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