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Title: | Machine Learning Approaches for Early Diagnosis and Prediction of Fetal Abnormalities |
Authors: | R.Chinnaiyan |
Keywords: | Computer Science / Information Science |
Issue Date: | Jun-2021 |
Publisher: | IEEE Xplore |
Abstract: | Fetal Health denotes the health and growth of the fetal and frequent contacts in the uterus of the pregnant women during pregnancy. Maximum pregnancy period complexities leads fetal to a severe difficulty which limits right growth that causes deficiency or death. Harmless pregnancy period by predicting the risk levels before the occasion of difficulties boost right fetal growth. Forecasting the fetal health and growth state from a set of pre-classified patterns knowledge is vital in developing a predictive classifier model using Machine Learning Algorithms. |
URI: | http://localhost:8080/xmlui/handle/123456789/6651 |
Appears in Collections: | 2021 |
Files in This Item:
File | Description | Size | Format | |
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7. PAPER7ISE.pdf | 179.7 kB | Adobe PDF | View/Open |
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