Name
Abstract | ||
|---|---|---|
Efficient planning of hospital resources and services are the prime concern of any hospital administration in terms of patient care. Predicting Average Length of Stay of patient may help in strategic decision making and effective planning of hospital resources. If the length of stay is decided corresponding to disease treatment patient can plan their hospital days priorly in an efficient manner. In this research work, we have taken Alabama University historical hospital data set of the year 2008 and 2009 month-wise for the forecasting analysis using genetic crossover method. We have evaluated results in terms of Average Forecasting Error Rate (AFER) and Mean Square Error (MSE) values. Aim of this research is to forecast values using genetic approach. The calculated AFER value is compared with existing soft computing models which are evaluated over same data set. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IC3.2016.7880236 | 2016 Ninth International Conference on Contemporary Computing (IC3) |
Keywords | Field | DocType |
Time series data,genetic algorithm,AFER,MSE,average LOS of inpatient | Prime (order theory),Time series,Computer science,Mean squared error,Artificial intelligence,Soft computing,Health administration,Genetic algorithm,Crossover,Pattern recognition,Word error rate,Operations research,Statistics | Conference |
ISSN | ISBN | Citations |
2572-6110 | 978-1-5090-3252-5 | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Garima Sharma | 1 | 0 | 0.34 |
| Saurabh Srivastava | 2 | 184 | 19.27 |