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

Publication2026

Multi-Model Feature Fusion-based Ensemble of Pre-trained CNNs for Chest X-ray Classification

The record

Type
Publication
Date
1 January 2026
Level
National
Journal
Proceeding of International Conference on Computing Communication Control and Cyber Physical Systems I5cps 2026
Published
1 January 2026
DOI
10.1109/i5cps67958.2026.11452407
Scopus ID
105037451186
Authors
6
Open access
No
Citations
0
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

    Ensemble deep learning framework for chest X-ray classification achieving 98.88% accuracy, enabling automated disease diagnosis and improving healthcare decision support.

    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 Empowered Indians

    ThemePrimaryHigh confidenceJudged

    Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Ensemble deep learning framework for chest X-ray classification achieving 98.88% accuracy, enabling automated disease diagnosis and improving healthcare decision support.

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

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KIIT Deemed to be University. “Multi-Model Feature Fusion-based Ensemble of Pre-trained CNNs for Chest X-ray Classification”. Kortex.

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