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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
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21470
Article Published : 8508
Total Authors : 22383
Total Reviewer : 805
Total Countries : 157
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| Paper Title: | A Machine Learning Approach Using Statistical Models Early Detection of Cardiac Arrest In Newborn Babies In The Cardiac Intensive Care Unit |
| Authors Name: | Mr. K. Lakshmi Kanth Reddy |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_189709
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| Published Paper Id: | IJRTI2404147 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| Abstract: | Detecting cardiac arrest in newborn babies is a critical medical emergency requiring swift intervention. Recent research has focused on identifying potential indicators and biomarkers to enable early detection. Various imaging techniques, including echocardiography and computed tomography, are being explored for this purpose. A Cardiac Machine Learning model (CMLM) has been developed utilizing statistical models to aid in early detection within the Cardiac Intensive Care Unit (CICU). By combining neonatal physiological parameters, cardiac arrest events can be predicted using techniques such as logistic regression and support vector machines. |
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| Cite Article: | "A Machine Learning Approach Using Statistical Models Early Detection of Cardiac Arrest In Newborn Babies In The Cardiac Intensive Care Unit", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1090 - 1098, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404147.pdf |
| Downloads: | 000205386 |
| ISSN: |
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: IJRTI2404147
Registration ID:189709
Published In: Volume 9 Issue 4, April-2024
DOI (Digital Object Identifier):
Page No: 1090 - 1098 Country: Hyderabad, Telanagana, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2404147 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2404147 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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