Population health and vulnerable populations have an impact on the overall health status of communities and countries. This requires recognition that we have serious disparities in health delivery and outcomes that must be addressed in all healthcare settings. The nursing profession has acknowledged these facts through its recent standards and ethics; statements about racism, discrimination, health equity, and disparities; and strategies to improve population health. Designed to support current standards and goals for the nursing profession, Health Equity and Disparities provides students with a succinct yet vital exploration of health disparities, their impact on health systems, and the ways in which nursing professionals can promote more equitable health experiences. The text addresses a broad range of topics, including social determinants of health; social justice and economics; diversity and disparities; and health literacy. Readers learn about the promotion of diversity, inclusivity, and equity in nursing, as well as the impact of health and social policies on health equity and disparities. They are provided with strategies to improve and sustain greater levels of health equity through collaboration, partnerships, and transformative change. Health Equity and Disparities is part of the Cognella Series on Public and Community Health Nursing, a collection of concise, informative guides that explore critical topical areas, their nursing application, and their relationship to nursing practice.

All too often, individuals engaged in the biomedical sciences assume that numeric data must be left to the proper authorities (e.g., statisticians and data analysts) who are trained to apply sophisticated mathematical algorithms to sets of data. This is a terrible mistake. Individuals with keen observational skills, regardless of their mathematical training, are in the best position to draw correct inferences from their own data and to guide the subsequent implementation of robust, mathematical analyses. Volume 2 of Logic and Critical Thinking in the Biomedical Sciences provides readers with a repertoire of deductive non-mathematical methods that will help them draw useful inferences from their own data. Volumes 1 and 2 of Logic and Critical Thinking in the Biomedical Sciences are written for biomedical scientists and college-level students engaged in any of the life sciences, including bioinformatics and related data sciences.

Concepts and Experimental Protocols of Modelling and Informatics in Drug Design discusses each experimental protocol utilized in the field of bioinformatics, focusing especially on computer modeling for drug development. It helps the user in understanding the field of computer-aided molecular modeling (CAMM) by presenting solved exercises and examples. The book discusses topics such as fundamentals of molecular modeling, QSAR model generation, protein databases and how to use them to select and analyze protein structure, and pharmacophore modeling for drug targets. Additionally, it discusses data retrieval system, molecular surfaces, and freeware and online servers. The book is a valuable source for graduate students and researchers on bioinformatics, molecular modeling, biotechnology and several members of biomedical field who need to understand more about computer-aided molecular modeling.