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

Publication2025

Gastrointestinal Lung Cancer Disease Classification via Hybrid Deep Architecture Trained with Improved Pattern Features

The record

Type
Publication
Date
1 January 2025
Level
National
Journal
Esic 2025 5th International Conference on Emerging Systems and Intelligent Computing Proceedings
Pages
51-57
Published
1 January 2025
DOI
10.1109/esic64052.2025.10962725
Scopus ID
105004552237
Authors
5
Open access
No
Citations
0
International co-authorship
No
Co-author countries
IN

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being

    TargetPrimaryHigh confidenceJudged

    Hybrid deep learning architecture combining SqueezeNet and LSTM for gastrointestinal lung cancer classification demonstrates medical AI innovation.

    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

  2. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetSecondaryHigh confidenceJudged

    Novel hybrid neural network topology represents research innovation in deep learning for cancer image classification.

    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

    Cancer diagnosis AI supports early detection and improved treatment outcomes for gastrointestinal and lung malignancies.

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

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KIIT Deemed to be University. “Gastrointestinal Lung Cancer Disease Classification via Hybrid Deep Architecture Trained with Improved Pattern Features”. Kortex.

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Gastrointestinal Lung Cancer Disease Classification via Hybrid Deep Architecture Trained with Improved Pattern Features · Kortex