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Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis

Igor Barišić ; Department of Diagnostical and Interventional Radiology, Clinical Hospital Split, Šoltanska 1, 21000 Split, Croatia
Vladimir Wilhelm ; Division of Nephrology, Department of Internal Medicine, Clinical Hospital Split, Šoltanska 1, 21000 Split, Croatia
Nikola Štambuk ; Rudjer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia
Ksenija Karaman ; Department of Ophthalmology, Clinical Hospital Split, Šoltanska 1, 21000 Split, Croatia
Stipan Janković ; Department of Diagnostical and Interventional Radiology, Clinical Hospital Split, Šoltanska 1, 21000 Split, Croatia
Paško Konjevoda ; Rudjer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia
Biserka Pokrić ; Rudjer Bošković Institute, Bijenička cesta 54, 10000 Zagreb, Croatia

Puni tekst: engleski, pdf (72 KB) str. 935-944 preuzimanja: 199* citiraj
APA 6th Edition
Barišić, I., Wilhelm, V., Štambuk, N., Karaman, K., Janković, S., Konjevoda, P. i Pokrić, B. (2002). Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis. Croatica Chemica Acta, 75 (4), 935-944. Preuzeto s https://hrcak.srce.hr/131755
MLA 8th Edition
Barišić, Igor, et al. "Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis." Croatica Chemica Acta, vol. 75, br. 4, 2002, str. 935-944. https://hrcak.srce.hr/131755. Citirano 30.11.2021.
Chicago 17th Edition
Barišić, Igor, Vladimir Wilhelm, Nikola Štambuk, Ksenija Karaman, Stipan Janković, Paško Konjevoda i Biserka Pokrić. "Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis." Croatica Chemica Acta 75, br. 4 (2002): 935-944. https://hrcak.srce.hr/131755
Harvard
Barišić, I., et al. (2002). 'Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis', Croatica Chemica Acta, 75(4), str. 935-944. Preuzeto s: https://hrcak.srce.hr/131755 (Datum pristupa: 30.11.2021.)
Vancouver
Barišić I, Wilhelm V, Štambuk N, Karaman K, Janković S, Konjevoda P i sur. Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis. Croatica Chemica Acta [Internet]. 2002 [pristupljeno 30.11.2021.];75(4):935-944. Dostupno na: https://hrcak.srce.hr/131755
IEEE
I. Barišić, et al., "Machine Learning Based Analysis of Biochemical and Morphologic Parameters in Patients with Dialysis Related Amyloidosis", Croatica Chemica Acta, vol.75, br. 4, str. 935-944, 2002. [Online]. Dostupno na: https://hrcak.srce.hr/131755. [Citirano: 30.11.2021.]

Sažetak
Dialysis related amyloidosis is the accumulation and deposition of P2-microglobulin derived fibrils in bones and joints, due to insufficient elimination during therapy or slowly progressing renal failure. The aim of this Study was to analyse biochemical, morphologic and anamnestic parameters that may be relevant for the onset and developement of dialysis related amyloidosis. In addition to standard statistical procedures, we also applied the machine-learning based methods of data mining to quantify the risk factors for asymptomatic patients. Extraction of risk factors for the onset of the dialysis related amyloidosis syndrome could enable the clinician to predict the symptoms and consider medical procedures to prevent the onset of the disease. The C4.5 machine learning algorithm extracted a simple and highly accurate tree for discrimination of asymptomatic and symptomatic patients suffering from dialysis related amyloidosis. It remains an open question if our findings may contribute to the problem of accurately predicting the onset of dialysis related arthropathy in the asymptomatic patient group.

Ključne riječi
dialysis; amyloidosis; biochemistry; morphologic parameters; shoulder; knee; symptoms

Hrčak ID: 131755

URI
https://hrcak.srce.hr/131755

Posjeta: 400 *