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Title: :  PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION
PaperId: :  26124
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 11 Issue 2 2025
DUI:    16.0415/IJARIIE-26124
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
D ViswasahithyaSIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
B.SHIVARAMSIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
K.DIVYA TEJASIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
B.VINEELASIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
B. SIREESHASIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY
V. TILAKSIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY

Abstract

INFORMATION TECHNOLOGY
Heart failure prediction, newborn healthcare, early diagnosis, machine learning, decision tree, random forest, logistic regression, XGBoost, medical AI, neonatal care, healthcare automation, clinical decision support.
The early detection of heart failure in newborn babies is critical to improving their health outcomes. Newborns are vulnerable to various life-threatening conditions, including heart failure, which can often go undiagnosed due to the subtle nature of early symptoms. Timely detection and intervention are essential for reducing mortality rates and enhancing the quality of care. However, traditional methods of diagnosis can be slow and inefficient, making it crucial to explore machine learning as a tool for automating the detection process. This project seeks to bridge the gap by utilizing machine learning algorithms—specifically Decision Tree, Random Forest, Logistic Regression, and XGBoost—to predict heart failure in newborns. By applying these models, healthcare professionals can make quicker and more accurate decisions. The motivation behind this project is to leverage advanced technologies to support doctors in their efforts to provide optimal care for newborns, ultimately leading to better health outcomes, reduced complications, and lower healthcare costs.

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IJARIIE D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. "PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION" International Journal Of Advance Research And Innovative Ideas In Education Volume 11 Issue 2 2025 Page 1350-1357
MLA D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. "PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION." International Journal Of Advance Research And Innovative Ideas In Education 11.2(2025) : 1350-1357.
APA D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, & V. TILAK. (2025). PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION. International Journal Of Advance Research And Innovative Ideas In Education, 11(2), 1350-1357.
Chicago D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. "PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION." International Journal Of Advance Research And Innovative Ideas In Education 11, no. 2 (2025) : 1350-1357.
Oxford D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. 'PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION', International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, 2025, p. 1350-1357. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/PREDICTING_NEONATAL_CARDIAC_ARREST_IN_THE_CICU__A_STATISTICAL_MACHINE_LEARNING_APPROACH_FOR_EARLY_INTERVENTION_ijariie26124.pdf (Accessed : ).
Harvard D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. (2025) 'PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION', International Journal Of Advance Research And Innovative Ideas In Education, 11(2), pp. 1350-1357IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/PREDICTING_NEONATAL_CARDIAC_ARREST_IN_THE_CICU__A_STATISTICAL_MACHINE_LEARNING_APPROACH_FOR_EARLY_INTERVENTION_ijariie26124.pdf (Accessed : )
IEEE D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK, "PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION," International Journal Of Advance Research And Innovative Ideas In Education, vol. 11, no. 2, pp. 1350-1357, Mar-App 2025. [Online]. Available: https://ijariie.com/AdminUploadPdf/PREDICTING_NEONATAL_CARDIAC_ARREST_IN_THE_CICU__A_STATISTICAL_MACHINE_LEARNING_APPROACH_FOR_EARLY_INTERVENTION_ijariie26124.pdf [Accessed : ].
Turabian D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. "PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 11 number 2 ().
Vancouver D Viswasahithya, B.SHIVARAM, K.DIVYA TEJA, B.VINEELA, B. SIREESHA, and V. TILAK. PREDICTING NEONATAL CARDIAC ARREST IN THE CICU: A STATISTICAL MACHINE LEARNING APPROACH FOR EARLY INTERVENTION. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2025 [Cited : ]; 11(2) : 1350-1357. Available from: https://ijariie.com/AdminUploadPdf/PREDICTING_NEONATAL_CARDIAC_ARREST_IN_THE_CICU__A_STATISTICAL_MACHINE_LEARNING_APPROACH_FOR_EARLY_INTERVENTION_ijariie26124.pdf
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