CLABSI Prevention Through AI-Powered Web Application Approach

Registration ID: IJNRD_207893

Published ID: IJNRD2310404

DOI: Click Here to Get

Aamir Dayma , Soniya Jain

CLABSI, machine learning, web application, healthcare, prediction, prevention, data collection, data processing, healthcare-associated infections

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.

Published Paper   E-Certificate

Aamir Dayma & Soniya Jain (October-2023). CLABSI Prevention Through AI-Powered Web Application Approach. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(10), e44-e50. https://ijnrd.org/papers/IJNRD2310404.pdf

Volume 8 Issue 10, October-2023

Pages : e44-e50

Paper Reg. ID: IJNRD_207893

Published Paper Id: IJNRD2310404

Downloads: 000121986

Research Area: Computer Engineering 

Country: Ankleshwar, GUJARAT, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2310404.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2310404

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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