International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
Submit Research Paper Join as a Reviewer

Plagiarism is checked by the leading plagiarism checker TurnItIn

Call for Paper

Volume 7 Issue 2
March-April 2025

Submit your research paper

Indexing Partners
Academia Advanced Sciences Index Bielefeld Academic Search Engine CiteSeer DRJI Google Scholar Independent Search Engine & Directory Network ISI (International Scientific Indexing) Issuu Mendeley Research Networks
RefSeek ResearcherId - Thomson Reuters ResearchGate Scirus Scribd Semantic Scholar UTeM - Universiti Teknikal Malaysia Melaka Wiki for Call for Papers WorldCat Zenodo

Real-Time AI Systems for ICU Risk Monitoring

Author(s) Mr. Zhaid Khan
Country India
Abstract Intensive Care Units (ICUs) play a critical role in the management of patients with life-threatening conditions. Early identification of risks such as sepsis, respiratory failure, and cardiac arrest can significantly improve patient outcomes. Traditional monitoring systems, however, rely on periodic assessments and manual interventions, which may not be sufficient for timely risk detection. Artificial Intelligence (AI) has emerged as a powerful tool in overcoming these limitations, enabling real-time, data-driven risk prediction and management. This paper explores the role of AI in transforming ICU risk monitoring through real-time predictive analytics. By leveraging machine learning, deep learning, and sensor technologies, AI systems can process vast amounts of patient data, offering early detection of complications, prioritizing high-risk patients, and supporting decision-making. The paper discusses the integration of AI into existing ICU frameworks, the components of AI-powered monitoring systems, their real-world applications, and the impact on patient care. Despite its transformative potential, the paper also addresses the challenges of data privacy, system integration, accuracy, and clinician adoption. Finally, the paper explores future directions, including the potential for AI to integrate with other ICU technologies and predict long-term outcomes. Through continuous innovation and rigorous validation, AI-driven monitoring has the potential to revolutionize ICU care by enhancing patient safety, optimizing resource allocation, and improving clinical outcomes.
Field Biology > Genetics / Molecular
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-14
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.41428
Short DOI https://doi.org/g9fm3n
View / Download PDF File

Share this



E-ISSN 2582-2160
CrossRef

CrossRef DOI is assigned to each research paper published in our journal.

IJFMR DOI prefix is
10.36948/ijfmr

Downloads
Research Paper Format Copyright Permission Form and Undertaking Form Cover Page Vol 7 Isu 2Cover Page Vol 7 Isu 1Cover Page Vol 6 Isu 6

All research papers published on this website are licensed under Creative Commons Attribution-ShareAlike 4.0 International License, and all rights belong to their respective authors/researchers.

CC-BY-SA Open Access

About IJFMR
Fees & Payment
Current Issue
Publication Archive 		Submit Research Paper
Track Submission Status
Publication Guidelines
Publication Ethics
Peer Review & Plagiarism 		Join as a Reviewer
Editors & Reviewers
Reviewer Referral Program
Get Reviewer Membership Certi. 		Website/Journal Policies
Usage Policy
Content Policies
Privacy Policy
Contact Us +91-9687-828-838 editor@ijfmr.com