prikaz prve stranice dokumenta Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model
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Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model
Croatian Medical Journal, 65 (2024), 2; 122-137. https://doi.org/10.3325/cmj.2024.65.122
Romić, Dominik; Berecki, Monika; Srakočić, Sanja; Josić Dominović, Paula; Justić, Helena; Hamer, Dominik; Petrinec, Daniela; Radmilović, Marina; Hackenberger, Branimir; Gajović, Srećko; Glasnović, Anton

Institucijski repozitorij: Dr Med - digitalni repozitorij Medicinskog fakulteta Sveučilišta u Zagrebu

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Romić, D., Berecki, M., Srakočić, S., Josić Dominović, P., Justić, H., Hamer, D. ... Glasnović, A. (2024). Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model. Croatian Medical Journal, 65. (2), 122-137. doi: 10.3325/cmj.2024.65.122

Romić, Dominik, et al. "Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model." Croatian Medical Journal, vol. 65, br. 2, 2024, str. 122-137. https://doi.org/10.3325/cmj.2024.65.122

Romić, Dominik, Monika Berecki, Sanja Srakočić, Paula Josić Dominović, Helena Justić, Dominik Hamer, Daniela Petrinec, et al. "Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model." Croatian Medical Journal 65, br. 2 (2024): 122-137. https://doi.org/10.3325/cmj.2024.65.122

Romić, D., et al. (2024) 'Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model', Croatian Medical Journal, 65(2), str. 122-137. doi: 10.3325/cmj.2024.65.122

Romić D, Berecki M, Srakočić S, Josić Dominović P, Justić H, Hamer D, i sur.. Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model. Croatian Medical Journal [Internet]. 30.04.2024. [pristupljeno 26.11.2024.];65(2):122-137. doi: 10.3325/cmj.2024.65.122

D. Romić, et al., "Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model", Croatian Medical Journal, vol. 65, br. 2, str. 122-137, Travanj 2024. [Online]. Dostupno na: https://urn.nsk.hr/urn:nbn:hr:105:242122. [Citirano: 26.11.2024.]

Za citiranje koristite ovu mrežnu adresu: https://urn.nsk.hr/urn:nbn:hr:105:242122
Podaci o radu
Naslov (engleski)Innovative statistical approaches: the use of neural networks reduces the sample size in the splenectomy-MCAO mouse model
AutorDominik Romić
AutorMonika Berecki
AutorSanja Srakočić
AutorPaula Josić Dominović
AutorHelena Justić
AutorDominik Hamer
AutorDaniela Petrinec
AutorMarina Radmilović
AutorBranimir Hackenberger
AutorSrećko Gajović
AutorAnton Glasnović
Autorova ustanovaSveučilište u Zagrebu
Medicinski fakultet
(HRVATSKI INSTITUT ZA ISTRAŽIVANJE MOZGA)
Autorova ustanovaSveučilište u Zagrebu
Medicinski fakultet
(KATEDRA ZA HISTOLOGIJU I EMBRIOLOGIJU)
Znanstveno / umjetničko
područje, polje i grana		BIOMEDICINA I ZDRAVSTVO
Temeljne medicinske znanosti
Citologija, histologija i embriologija
Znanstveno / umjetničko
područje, polje i grana		BIOMEDICINA I ZDRAVSTVO
Temeljne medicinske znanosti
Neuroznanost
Sažetak (engleski)
Aim: To compare the effectiveness of artificial neural network (ANN) and traditional statistical analysis on identical data sets within the splenectomy-middle carotid artery occlusion (MCAO) mouse model. Methods: Mice were divided into the splenectomized (SPLX) and sham-operated (SPLX-sham) group. A splenectomy was conducted 14 days before middle carotid artery occlusion (MCAO). Magnetic resonance imaging (MRI), bioluminescent imaging, neurological scoring (NS), and histological analysis, were conducted at two, four, seven, and 28 days after MCAO. Frequentist statistical analyses and ANN analysis employing a multi-layer perceptron architecture were performed to assess the probability of discriminating between SPLX and SPLX-sham mice. Results: Repeated measures ANOVA showed no significant differences in body weight (F (5, 45)=0.696, P=0.629), NS (F (2.024, 18.218)=1.032, P=0.377) and brain infarct size on MRI between the SPLX and SPLX-sham groups post-MCAO (F (2, 24)=0.267, P=0.768). ANN analysis was employed to predict SPLX and SPL-sham classes. The highest accuracy in predicting SPLX class was observed when the model was trained on a data set containing all variables (0.7736±0.0234). For SPL-sham class, the highest accuracy was achieved when it was trained on a data set excluding the variable combination MR contralateral/animal mass/NS (0.9284±0.0366). Conclusion: This study validated the neuroprotective impact of splenectomy in an MCAO model using ANN for data analysis with a reduced animal sample size, demonstrating the potential for leveraging advanced statistical methods to minimize sample sizes in experimental biomedical research.
Ključne riječi (engleski)
Jezikengleski
Vrsta publikacijeZnanstveni rad - Izvorni znanstveni rad
Status objaveObjavljen
Vrsta recenzijeRecenziran
Verzija publikacijeObjavljena verzija rada (izdavačev PDF)
Naslov časopisaCroatian Medical Journal
Brojčani podacivol. 65, br. 2, str. 122-137
p-ISSN0353-9504
e-ISSN1332-8166
DOIhttps://doi.org/10.3325/cmj.2024.65.122
URN:NBNurn:nbn:hr:105:242122
Datum objave publikacije2024-04-30
URL dokumentahttp://www.cmj.hr/2024/65/2/38706238.htm
Vrsta resursaTekst
Prava pristupaOtvoreni pristup
Uvjeti korištenjaIkona licence Imenovanje-Nekomercijalno-Bez prerada 4.0 međunarodna (CC BY-NC-ND 4.0)
Datum i vrijeme pohrane2024-06-20 11:04:53