Academic Journal
Emergency patient forecasting with models based on support vector machines
| العنوان: | Emergency patient forecasting with models based on support vector machines |
|---|---|
| المؤلفون: | Hernandez, Carlos, Lagos, Dafne, Leal, Paola, Castillo, Jaime |
| المصدر: | IAES International Journal of Artificial Intelligence (IJ-AI); Vol 13, No 3: September 2024; 3129-3140 ; 2252-8938 ; 2089-4872 ; 10.11591/ijai.v13.i3 |
| بيانات النشر: | Institute of Advanced Engineering and Science |
| سنة النشر: | 2024 |
| مصطلحات موضوعية: | Emergency Patient Forecasting with Models Based on Support Vector Machines, Emergency room, Forecasting, Linear regression, Machine learning, Support vector machine |
| الوصف: | Understanding the dynamic nature of the influx of patients is crucial for efficiently managing supplies, medical personnel, and infrastructure in an emergency room (ER). While overestimation can lead to resource wastage, underestimation can result in shortages and compromised service quality. This study addresses emergency patient forecast by means of implementing support vector machine (SVM) algorithms. Along four phases (analysis, design, development, and validation), more than 50,000 ER records were preprocessed and analyzed. Traditional error metrics such as mean absolute error (MAE), mean square error (MSE), root mean square error (RMSE), and mean absolute percentage error (MAPE) were utilized alongside monthly consolidated forecasts. To benchmark performance, actual values and forecasts derived from linear regression (LR) models were used. Experiments revealed that LR models had lower errors compared to SVM models. However, monthly consolidated forecasts showed that SVM-based models underestimated less than LR-based models. In conclusion, SVM-based models could help planners to accurately estimate the requirements for supplies and medical personnel during the period under study. |
| نوع الوثيقة: | article in journal/newspaper |
| وصف الملف: | application/pdf |
| اللغة: | English |
| Relation: | https://ijai.iaescore.com/index.php/IJAI/article/view/24906/14122; https://ijai.iaescore.com/index.php/IJAI/article/view/24906 |
| DOI: | 10.11591/ijai.v13.i3.pp3129-3140 |
| الاتاحة: | https://ijai.iaescore.com/index.php/IJAI/article/view/24906 https://doi.org/10.11591/ijai.v13.i3.pp3129-3140 |
| Rights: | Copyright (c) 2024 Institute of Advanced Engineering and Science ; http://creativecommons.org/licenses/by-sa/4.0 |
| رقم الانضمام: | edsbas.8C44FF8C |
| قاعدة البيانات: | BASE |
| DOI: | 10.11591/ijai.v13.i3.pp3129-3140 |
|---|