Augmentative and alternative communicationAugmentative and alternative communication (AAC) encompasses the communication methods used to supplement or replace speech or writing for those with impairments in the production or comprehension of spoken or written language. AAC is used by those with a wide range of speech and language impairments, including congenital impairments such as cerebral palsy, intellectual impairment and autism, and acquired conditions such as amyotrophic lateral sclerosis and Parkinson's disease.
Data analysisData analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientific and helping businesses operate more effectively.
End-of-life careEnd-of-life care refers to health care provided in the time leading up to a person's death. End-of-life care can be provided in the hours, days, or months before a person dies and encompasses care and support for a person's mental and emotional needs, physical comfort, spiritual needs, and practical tasks. EoLC is most commonly provided at home, in the hospital, or in a long-term care facility with care being provided by family members, nurses, social workers, physicians, and other support staff.
Geneva ConventionsThe Geneva Conventions are four treaties, and three additional protocols, that establish international legal standards for humanitarian treatment in war. The singular term Geneva Convention usually denotes the agreements of 1949, negotiated in the aftermath of the Second World War (1939–1945), which updated the terms of the two 1929 treaties and added two new conventions. The Geneva Conventions extensively define the basic rights of wartime prisoners, civilians and military personnel, established protections for the wounded and sick, and provided protections for the civilians in and around a war-zone.
Exploratory data analysisIn statistics, exploratory data analysis (EDA) is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling and thereby contrasts traditional hypothesis testing. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments.
Ambulatory careAmbulatory care or outpatient care is medical care provided on an outpatient basis, including diagnosis, observation, consultation, treatment, intervention, and rehabilitation services. This care can include advanced medical technology and procedures even when provided outside of hospitals. Ambulatory care sensitive conditions (ACSC) are health conditions where appropriate ambulatory care prevents or reduces the need for hospital admission (or inpatient care), such as diabetes or chronic obstructive pulmonary disease.
Principal component analysisPrincipal component analysis (PCA) is a popular technique for analyzing large datasets containing a high number of dimensions/features per observation, increasing the interpretability of data while preserving the maximum amount of information, and enabling the visualization of multidimensional data. Formally, PCA is a statistical technique for reducing the dimensionality of a dataset. This is accomplished by linearly transforming the data into a new coordinate system where (most of) the variation in the data can be described with fewer dimensions than the initial data.
Data qualityData quality refers to the state of qualitative or quantitative pieces of information. There are many definitions of data quality, but data is generally considered high quality if it is "fit for [its] intended uses in operations, decision making and planning". Moreover, data is deemed of high quality if it correctly represents the real-world construct to which it refers. Furthermore, apart from these definitions, as the number of data sources increases, the question of internal data consistency becomes significant, regardless of fitness for use for any particular external purpose.
