CI for a DSS to predict nursing coverage in a geriatric care facility.
The vast and growing area of informatics presents the single biggest change in how societies grow, work, and live. Strong emphasis is placed on environment, work safety, disease minimization, illness detection, and care interventions. The informatics in these areas is not adequately used to realize the full benefits to society, but using computational intelligence or soft computing techniques, we obtain a closer acceptance of confidence in the application of informatics to improve quality of life. There is a vast array of applications of informatics in society like bioinformatics, genetic detection, medical diagnosis, manufacturing, environmental responsibility, transportation design, etc. By using neural networks and genetic algorithms, reasoning on the data sources can result in emerging nursing informatics patterns where prediction can become more and more accurate in an acuity system that ultimately gives effective therapeutic care and decreased rates of mortality. In this paper, I propose the use of CI techniques to determine crisp data that can be incorporated into decision-making for nursing care.
Johnson
William Gregory
WG
EchelonGate. LLC, Atlanta, Georgia, USA.
D000368:Aged; D020000:Decision Support Systems, Clinical / Q000458:organization & administration*; D005851:Geriatric Nursing / Q000458:organization & administration*; D006299:Health Services for the Aged; D006801:Humans; D048108:Nursing Informatics; D014481:United States