INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (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)
In this paper, we present a new approach to preventing Central Line-Associated Bloodstream Infection (CLABSI) by integrating artificial intelligence (AI) into a web application developed using the MERN (MongoDB, Express, React, Node.js) stack. Our system combines data collection and surveillance, enabling healthcare professionals to input infection-related data through the web application. The application processes and analyzes this data using machine learning models to predict and identify potential CLABSI risks. By automating the surveillance process, the AI-powered web application offers an efficient and proactive solution for early detection and prevention of CLABSI, ultimately improving patient safety in healthcare settings.
Keywords:
CLABSI, machine learning, web application, healthcare, prediction, prevention, data collection, data processing, healthcare-associated infections
Cite Article:
"CLABSI Prevention Through AI-Powered Web Application Approach", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 10, page no.e44-e50, October-2023, Available :http://www.ijnrd.org/papers/IJNRD2310404.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 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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