United States Public Health ServiceThe United States Public Health Service (USPHS or PHS) is a collection of agencies of the Department of Health and Human Services concerned with public health, containing nine out of the department's twelve operating divisions. The Assistant Secretary for Health oversees the PHS. The Public Health Service Commissioned Corps (PHSCC) is the federal uniformed service of the PHS, and is one of the eight uniformed services of the United States. PHS had its origins in the system of marine hospitals that originated in 1798.
Mixture modelIn statistics, a mixture model is a probabilistic model for representing the presence of subpopulations within an overall population, without requiring that an observed data set should identify the sub-population to which an individual observation belongs. Formally a mixture model corresponds to the mixture distribution that represents the probability distribution of observations in the overall population.
Professional degrees of public healthThe Master of Public Health or Master of Philosophy in Public Health (MPH), Master of Science in Public Health (MSPH), Master of Medical Science in Public Health (MMSPH) and the Doctor of Public Health (DrPH), International Masters for Health Leadership (IMHL) are interdisciplinary professional degrees awarded for studies in areas related to public health. The MPH degree focuses on public health practice, as opposed to research or teaching.
Latent and observable variablesIn statistics, latent variables (from Latin: present participle of lateo, “lie hidden”) are variables that can only be inferred indirectly through a mathematical model from other observable variables that can be directly observed or measured. Such latent variable models are used in many disciplines, including political science, demography, engineering, medicine, ecology, physics, machine learning/artificial intelligence, bioinformatics, chemometrics, natural language processing, management, psychology and the social sciences.
Statistical classificationIn statistics, classification is the problem of identifying which of a set of categories (sub-populations) an observation (or observations) belongs to. Examples are assigning a given email to the "spam" or "non-spam" class, and assigning a diagnosis to a given patient based on observed characteristics of the patient (sex, blood pressure, presence or absence of certain symptoms, etc.). Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features.
