Araştırma Makalesi
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Yıl 2021, Cilt 9, Sayı 2, 178 - 186, 30.04.2021
https://doi.org/10.17694/bajece.782510

Öz

Kaynakça

  • Prof. (Dr) DP Sharma, http://dpsharma.info https://en.wikipedia.org/wiki/D.P._Sharma Ph.D.,FFSFE-Germany,FIACSIT-Singapore,DB2& WSAD IBM-USA

Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis

Yıl 2021, Cilt 9, Sayı 2, 178 - 186, 30.04.2021
https://doi.org/10.17694/bajece.782510

Öz

Medical doctors of today are challenged with increasingly large volumes of high-dimensional, heterogeneous and unstructured data from various sources that pose significant challenges for manual analysis. However, this unstructured data is mainly vital for decision making but there exists shortage of intelligent tools to extract the hidden knowledge. In view of these facts, application of machine learning methods in healthcare is a growing phenomenon. This paper explores machine learning approaches for interpreting large quantities of continuously acquired, multivariate patient based laboratory data, in intensive care unit (ICU) settings. The research hypothesizes that principal component analysis (PCA) can be able to capture the changes in the outcomes of applying medical interventions. We adopted PCA as a main method, to observe and capture the daily changes for intensive care unit patients. The approach will be able to inform the physicians, which laboratory tests are exhibiting variances after an intervention, and their associated epiphenomenon. This can be used as a clue to make decisions on which treatment or diagnosis to apply further. Experimental analysis results indicate that PCA was able to capture patient progression in terms of variances and permutation tests for the validity and stability of the model exhibits an acceptable significance level with a p-value of 0.001. Results showed that the approach provides promising results for interpreting large quantities of patient data for establishing a cause-effect relationship from medical interventions and be used as an early warning system. The study retrospectively demonstrated the capability of PCA to monitor and provide an alert to the clinicians about the patient’s changing conditions, thereby providing opportunities for timely interventions. If coupled with other machine learning models, the approach can also be able to support clinical decision making and enable an effective patient tailored care for better health outcomes.

Kaynakça

  • Prof. (Dr) DP Sharma, http://dpsharma.info https://en.wikipedia.org/wiki/D.P._Sharma Ph.D.,FFSFE-Germany,FIACSIT-Singapore,DB2& WSAD IBM-USA

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgisayar Bilimleri, Yapay Zeka
Yayınlanma Tarihi April 2021
Bölüm Araştırma Makalesi
Yazarlar

Mohammed Abebe YİMER> (Sorumlu Yazar)
DOKUZ EYLUL UNIVERSITY
0000-0003-0622-4841
Türkiye


Süleyman SEVİNÇ>
DOKUZ EYLUL UNIVERSITY
0000-0001-9052-5836
Türkiye


Ali Rıza ŞİŞMAN>
DOKUZ EYLUL UNIVERSITY
0000-0002-9266-0844
Türkiye


Özlem AKTAŞ Bu kişi benim
DOKUZ EYLUL UNIVERSITY
0000-0001-6415-0698
Türkiye


Oktay YILDIRIM>
DOKUZ EYLUL UNIVERSITY
0000-0001-7281-3623
Türkiye


Eminullah YAŞAR Bu kişi benim
DOKUZ EYLUL UNIVERSITY
0000-0003-2298-4808
Türkiye

Yayımlanma Tarihi 30 Nisan 2021
Yayınlandığı Sayı Yıl 2021, Cilt 9, Sayı 2

Kaynak Göster

Bibtex @araştırma makalesi { bajece782510, journal = {Balkan Journal of Electrical and Computer Engineering}, issn = {2147-284X}, address = {}, publisher = {Balkan Yayın}, year = {2021}, volume = {9}, number = {2}, pages = {178 - 186}, doi = {10.17694/bajece.782510}, title = {Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis}, key = {cite}, author = {Yimer, Mohammed Abebe and Sevinç, Süleyman and Şişman, Ali Rıza and Aktaş, Özlem and Yıldırım, Oktay and Yaşar, Eminullah} }
APA Yimer, M. A. , Sevinç, S. , Şişman, A. R. , Aktaş, Ö. , Yıldırım, O. & Yaşar, E. (2021). Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis . Balkan Journal of Electrical and Computer Engineering , 9 (2) , 178-186 . DOI: 10.17694/bajece.782510
MLA Yimer, M. A. , Sevinç, S. , Şişman, A. R. , Aktaş, Ö. , Yıldırım, O. , Yaşar, E. "Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis" . Balkan Journal of Electrical and Computer Engineering 9 (2021 ): 178-186 <https://dergipark.org.tr/tr/pub/bajece/issue/61773/782510>
Chicago Yimer, M. A. , Sevinç, S. , Şişman, A. R. , Aktaş, Ö. , Yıldırım, O. , Yaşar, E. "Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis". Balkan Journal of Electrical and Computer Engineering 9 (2021 ): 178-186
RIS TY - JOUR T1 - Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis AU - Mohammed AbebeYimer, SüleymanSevinç, Ali RızaŞişman, ÖzlemAktaş, OktayYıldırım, EminullahYaşar Y1 - 2021 PY - 2021 N1 - doi: 10.17694/bajece.782510 DO - 10.17694/bajece.782510 T2 - Balkan Journal of Electrical and Computer Engineering JF - Journal JO - JOR SP - 178 EP - 186 VL - 9 IS - 2 SN - 2147-284X- M3 - doi: 10.17694/bajece.782510 UR - https://doi.org/10.17694/bajece.782510 Y2 - 2021 ER -
EndNote %0 Balkan Journal of Electrical and Computer Engineering Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis %A Mohammed Abebe Yimer , Süleyman Sevinç , Ali Rıza Şişman , Özlem Aktaş , Oktay Yıldırım , Eminullah Yaşar %T Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis %D 2021 %J Balkan Journal of Electrical and Computer Engineering %P 2147-284X- %V 9 %N 2 %R doi: 10.17694/bajece.782510 %U 10.17694/bajece.782510
ISNAD Yimer, Mohammed Abebe , Sevinç, Süleyman , Şişman, Ali Rıza , Aktaş, Özlem , Yıldırım, Oktay , Yaşar, Eminullah . "Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis". Balkan Journal of Electrical and Computer Engineering 9 / 2 (Nisan 2021): 178-186 . https://doi.org/10.17694/bajece.782510
AMA Yimer M. A. , Sevinç S. , Şişman A. R. , Aktaş Ö. , Yıldırım O. , Yaşar E. Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis. Balkan Journal of Electrical and Computer Engineering. 2021; 9(2): 178-186.
Vancouver Yimer M. A. , Sevinç S. , Şişman A. R. , Aktaş Ö. , Yıldırım O. , Yaşar E. Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis. Balkan Journal of Electrical and Computer Engineering. 2021; 9(2): 178-186.
IEEE M. A. Yimer , S. Sevinç , A. R. Şişman , Ö. Aktaş , O. Yıldırım ve E. Yaşar , "Monitoring the Treatments and Interventions to Intensive Care Patients: A Study for Multidimensional Evaluation of Changes in Patient Test Results with Principal Component Analysis", Balkan Journal of Electrical and Computer Engineering, c. 9, sayı. 2, ss. 178-186, Nis. 2021, doi:10.17694/bajece.782510

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