Predicting risk factors associated with preterm delivery using a machine learning model.
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| Title: | Predicting risk factors associated with preterm delivery using a machine learning model. |
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| Authors: | Kavitha, S. N.1, kavijadhav86@gmail.com, Asha, V.1 |
| Source: | Multimedia Tools & Applications; Sep2024, Vol. 83 Issue 30, p74255-74280, 26p |
| Database: | Applied Science & Technology Source |
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| FullText | Links: – Type: pdflink Text: Availability: 1 |
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| Header | DbId: aci DbLabel: Applied Science & Technology Source An: 179395168 AccessLevel: 2 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=179395168 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11042-024-18332-7 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 74255 Titles: – TitleFull: Predicting risk factors associated with preterm delivery using a machine learning model. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Kavitha, S. N. – PersonEntity: Name: NameFull: Asha, V. IsPartOfRelationships: – BibEntity: Dates: – D: 21 M: 09 Text: Sep2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 13807501 Numbering: – Type: volume Value: 83 – Type: issue Value: 30 Titles: – TitleFull: Multimedia Tools & Applications Type: main |
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