o:33843 Predicting Thrombophilia using Neural Networks and Decision Trees en Abstract: The occurrence of thrombophilia during pregnancy results from a complex interaction of inherited and acquired factors, followed by an increase in blood coagulation and subsequent placental ischemic conditions. In this paper, a novel method is presented, whose aim is early identification of the risk of developing thrombophilia in pregnancy. The proposed method is based on machine learning algorithms: decision trees and neural networks. The research uses a dataset consisting of demographic, lifestyle, and clinical information from 35 pregnant women (22 healthy and 13 with thrombophilia). The results show the effectiveness of decision trees and neural networks in accurately predicting the risk of developing thrombophilia in pregnancy. The implications of this research are significant for clinical practice and it provides a valuable tool for early identifying women with high risk of thrombophilia in pregnancy that can enable improvement of preventive measures, such as lifestyle modifications and the use of therapeutic prophylaxis. In conclusion, this paper demonstrates the potential of machine learning algorithms for the prediction of thrombophilia in pregnancy. By combining advanced computational techniques with comprehensive datasets, we can enhance our understanding of thrombophilia in pregnancy risk factors and improve patient outcomes through personalized preventive measures. Keywords: neural networks, decision trees, machine learning, thrombophilia in pregnancy, and prediction 1552102 http://www.dunp.np.ac.rs/wp-content/uploads/2022/publikacije/serija-a/contents/vol.15no2-2023/SP-SUNP-15-2-23-4.pdf 2024-05-28T07:43:15.896Z 44 no 46 Aldina Avdić Državni univerzitet u Novom Pazaru 29219175 0000-0003-4312-3839 Nataša Đorđević Državni univerzitet u Novom Pazaru person 0000-0002-1100-5689 Ulfeta Marovac Državni univerzitet u Novom Pazaru person 86849033 0000-0001-7232-3755 Lejlija Memić Državni univerzitet u Novom Pazaru person 0000-0002-2692-6229 Zana Dolićanin Državni univerzitet u Novom Pazaru person 0000-0003-0457-3087 Goran Babić person 0000-0002-0837-7350 application/pdf 2266712 https://phaidrabg.bg.ac.rs/o:33843 no yes 1 70 92000001 20A01 SCIENTIFIC PUBLICATIONS OF THE STATE UNIVERSITY OF NOVI PAZAR, Series A: Applied Mathematics, Informatics & Mechanics 15 2 97 108 2023