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The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks

IJCCS (Indonesian Journal of Computing and Cybernetics Systems) · Vol. 1 No. 1 (2009)

DOI
10.22146/ijccs.20
ISSN
2460-7258, 1978-1520
Published
2009-06-14
Publisher
IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.
License
creativecommons.org/licenses/by-sa/4.0

Abstract

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.

Collaboration network of the authors

22 authors · 26 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Universitas Gadjah Mada
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Bambang Hendro SunarmintoAffiliation unknown1
Medhanita Dewi RenantiAffiliation unknown1
Juwita MaharantiAffiliation unknown1
Iqnatius Dimas NugrohoUniversitas Gadjah Mada1
Amelia NursantiUniversitas Gadjah Mada1
Tri Kuntoro PriyambodoUniversitas Gadjah Mada1
Zaied ShouranUniversitas Gadjah Mada1
Nur Azizul HaqimiUniversitas Gadjah Mada1
Sigit PriyantaUniversitas Gadjah Mada1
Friska Ayu ListyaUniversitas Gadjah Mada1
Wahyono WahyonoUniversitas Gadjah Mada1
Riska Amalia PraptiwiUniversitas Gadjah Mada1
Dayan Ramly RamadhanUniversitas Gadjah Mada1
Hendri Kurniawan PrakosaUniversitas Gadjah Mada1
Anindhita NisitasariUniversitas Gadjah Mada1
Raymond LuisUniversitas Gadjah Mada1
Sarah Rosdiana TambunanUniversitas Gadjah Mada1
Luthfia Nurma HapsariUniversitas Gadjah Mada1
Reka AlamsyahUniversitas Gadjah Mada1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.ugm.ac.id/ijccs/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks</dc:title>
	<dc:creator>Azis, Anifudin</dc:creator>
	<dc:creator>Rokhman, Nur</dc:creator>
	<dc:creator>Wibowo, Praretno</dc:creator>
	<dc:description xml:lang="en-US">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.</dc:description>
	<dc:publisher xml:lang="en-US">IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.</dc:publisher>
	<dc:date>2009-06-14</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US"></dc:type>
	<dc:identifier>https://journal.ugm.ac.id/ijccs/article/view/20</dc:identifier>
	<dc:identifier>10.22146/ijccs.20</dc:identifier>
	<dc:source xml:lang="en-US">IJCCS (Indonesian Journal of Computing and Cybernetics Systems); Vol 1, No 1 (2006): January</dc:source>
	<dc:source>2460-7258</dc:source>
	<dc:source>1978-1520</dc:source>
	<dc:rights xml:lang="en-US">Copyright (c) 2009 IJCCS - Indonesian Journal of Computing and Cybernetics Systems</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
</oai_dc:dc>