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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21686
Article Published : 8549
Total Authors : 22487
Total Reviewer : 811
Total Countries : 159
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| Paper Title: | COMPARATIVE ANALYTICS FOR OBSTETRIC DELIVERY METHODS USING MACHINE LEARNING ALGORITHMS |
| Authors Name: | Prof.Khallikkunaisa , Channakeshava D L , B Matheen , Chethan Kumar K B , Balasubramani |
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IJRTI_204168
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| Published Paper Id: | IJRTI2505303 |
| Published In: | Volume 10 Issue 5, May-2025 |
| DOI: | |
| Abstract: | Childbirth mode prediction is a critical aspect of obstetric care, aiding healthcare professionals in making informed decisions to ensure maternal safety. Traditional approaches rely on clinical expertise and heuristic-based risk assessment methods, which may not always generalize well across diverse populations. Recent advances in Machine Learning (ML) provide an opportunity to develop data driven predictive models that improve accuracy and support evidence-based decision-making to assist physicians in choosing the most effective delivery method, a number of models have been developed and compared, including the KNN, RF, SVM, Decision Tree, and a stochastic classifier. This study explores the application of machine learning (ML) algorithms for predicting the mode of childbirth based on patient data. We utilize various datasets containing demographic, clinical, and obstetric history features, including maternal age, gestational age, body mass index (BMI), medical conditions (e.g., diabetes or hypertension), previous delivery history, and fetal health indicators. |
| Keywords: | Childbirth prediction, machine learning, decision support system, delivery mode classification, maternal and infant health. |
| Cite Article: | "COMPARATIVE ANALYTICS FOR OBSTETRIC DELIVERY METHODS USING MACHINE LEARNING ALGORITHMS", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.d19-d23, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505303.pdf |
| Downloads: | 000435 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2505303
Registration ID:204168
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: d19-d23 Country: Bengaluru , Karnataka , India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505303 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505303 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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