The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks
The exact handling to the postoperative inpatient of the major operation in the restoration period, became one of the factors that very important for the success of the process of medical treatment on the whole. By paying attention to the development of signs and vital signs from the patient, could...
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Universitas Gadjah Mada
2009-06-01
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Series: | IJCCS (Indonesian Journal of Computing and Cybernetics Systems) |
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doaj-6c193ccf689845c783aebaac30d823982020-11-24T22:16:29ZengUniversitas Gadjah MadaIJCCS (Indonesian Journal of Computing and Cybernetics Systems)1978-15202460-72582009-06-011110.22146/ijccs.2020The Prediction of Medical Decision Post Operative of the Major Operation using Neural NetworksAnifudin AzisNur RokhmanPraretno WibowoThe exact handling to the postoperative inpatient of the major operation in the restoration period, became one of the factors that very important for the success of the process of medical treatment on the whole. By paying attention to the development of signs and vital signs from the patient, could be made medical by one decision took the form of the further action for the handling of the patient. Using backpropagation neural networks, could be made by a system that could carry out the prediction (forecast) the medical decision that will be taken to the postoperative patient the major's operation. After trining, by accepting sign input and the vital sign of the patient, the system could determine the action that will be carried out against the patient. From results of the test of the application program showed that the backpropagation neural networks could do the prediction of the medical decision with the success to 80%. Therefore, output from the system could be used as consideration of the doctor to decide the further action for the patient.https://jurnal.ugm.ac.id/ijccs/article/view/20 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Anifudin Azis Nur Rokhman Praretno Wibowo |
spellingShingle |
Anifudin Azis Nur Rokhman Praretno Wibowo The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks IJCCS (Indonesian Journal of Computing and Cybernetics Systems) |
author_facet |
Anifudin Azis Nur Rokhman Praretno Wibowo |
author_sort |
Anifudin Azis |
title |
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks |
title_short |
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks |
title_full |
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks |
title_fullStr |
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks |
title_full_unstemmed |
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks |
title_sort |
prediction of medical decision post operative of the major operation using neural networks |
publisher |
Universitas Gadjah Mada |
series |
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) |
issn |
1978-1520 2460-7258 |
publishDate |
2009-06-01 |
description |
The exact handling to the postoperative inpatient of the major operation in the restoration period, became one of the factors that very important for the success of the process of medical treatment on the whole. By paying attention to the development of signs and vital signs from the patient, could be made medical by one decision took the form of the further action for the handling of the patient. Using backpropagation neural networks, could be made by a system that could carry out the prediction (forecast) the medical decision that will be taken to the postoperative patient the major's operation. After trining, by accepting sign input and the vital sign of the patient, the system could determine the action that will be carried out against the patient. From results of the test of the application program showed that the backpropagation neural networks could do the prediction of the medical decision with the success to 80%. Therefore, output from the system could be used as consideration of the doctor to decide the further action for the patient. |
url |
https://jurnal.ugm.ac.id/ijccs/article/view/20 |
work_keys_str_mv |
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_version_ |
1725789616104013824 |