Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Highlights? IUGR risk estimation using noninvasive Doppler indices:PI s and RI s of UA, MCA and DV and AFI's are analyzed. ? The Doppler indices are applied to the SVM system to make a decision on the fetal llbeing. ? PI indices of UA, MCA and DV are stable and balanced indicators of IUGR at risk.  studies the risk of intrauterine compromise in the fetuses with intrauterine growth restriction (IUGR) using support vector machines (SVM). A structured and globally optimized SVM system may be preferable procedure in the identification of IUGR fetus at risk. The IUGR risk is estimated in two stages: In the first stage, noninvasive Doppler pulsatility index (PI) and resistance index (RI) of umbilical artery (UA), middle cerebral artery (MCA) and ductus venosus (DV), and amniotic fluid index (AFI) are retrospectively analyzed and the Doppler indices are applied to the SVM system to make a diagnosis decision on the fetal ll being as "reactive" or "nonreactive and/or fetal distress (FD)" on the nonstress test (NST) (training data). In the second stage (testing data), the decision is validated by the NST (target value). Experiments are performed in retrospective clinical situation. Forty-four preterm with IUGR and without IUGR pregnancies before 34 eks gestation are considered. Also, the nonparametric Bayes-risk decision rule, k-nearest neighbor (k-NN), is used for comparison. It is observed that the SVM system is proven to be useful in predicting the expected risk in IUGR cases in the small population study. Also, the PI and RI values of UA, MCA and DV are effective in distinguishing IUGR cases at risk.
['Fikret S. Gürgen', 'Zeynep Zengin', 'Füsun G. Varol']
I am writing a research paper on a idea Intrauterine growth restriction (IUGR) risk decision based on support vector machines
[{"from": "human", "value": "I am writing a research paper on a idea Intrauterine growth restriction (IUGR) risk decision based on support vector machines"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Highlights? IUGR risk estimation using noninvasive Doppler indices:PI s and RI s of UA, MCA and DV and AFI's are analyzed. ? The Doppler indices are applied to the SVM system to make a decision on the fetal llbeing. ? PI indices of UA, MCA and DV are stable and balanced indicators of IUGR at risk.  studies the risk of intrauterine compromise in the fetuses with intrauterine growth restriction (IUGR) using support vector machines (SVM). A structured and globally optimized SVM system may be preferable procedure in the identification of IUGR fetus at risk. The IUGR risk is estimated in two stages: In the first stage, noninvasive Doppler pulsatility index (PI) and resistance index (RI) of umbilical artery (UA), middle cerebral artery (MCA) and ductus venosus (DV), and amniotic fluid index (AFI) are retrospectively analyzed and the Doppler indices are applied to the SVM system to make a diagnosis decision on the fetal ll being as \"reactive\" or \"nonreactive and/or fetal distress (FD)\" on the nonstress test (NST) (training data). In the second stage (testing data), the decision is validated by the NST (target value). Experiments are performed in retrospective clinical situation. Forty-four preterm with IUGR and without IUGR pregnancies before 34 eks gestation are considered. Also, the nonparametric Bayes-risk decision rule, k-nearest neighbor (k-NN), is used for comparison. It is observed that the SVM system is proven to be useful in predicting the expected risk in IUGR cases in the small population study. Also, the PI and RI values of UA, MCA and DV are effective in distinguishing IUGR cases at risk."}]