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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2018

An improved method for detecting false alarm in arrhythmia ICU patients

The record

Type
Publication
Date
2 July 2018
Level
National
Journal
Proceedings 2018 4th IEEE International Conference on Research in Computational Intelligence and Communication Networks Icrcicn 2018
Pages
66-69
Published
2 July 2018
DOI
10.1109/icrcicn.2018.8718731
Scopus ID
85067131763
Authors
2
Open access
No
Citations
3
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 3 Ensure healthy lives and promote well-being for all at all ages

    GoalPrimaryHigh confidenceJudged

    Develops k-nearest neighbor classifier achieving 99.95% accuracy for distinguishing true cardiac arrhythmias from false alarms using ECG and arterial blood pressure data, reducing unnecessary alarm fatigue in intensive care units

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-1.2 Health and well-being

    Sub-themePrimaryHigh confidenceJudged

    Machine learning system improving cardiac patient safety and ICU monitoring outcomes

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “An improved method for detecting false alarm in arrhythmia ICU patients”. Kortex.

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