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

Publication2021

Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network

The record

Type
Publication
Date
1 March 2021
Level
International — held abroad
Journal
Information Processing and Management
Volume
58
Issue
2
Published
1 March 2021
DOI
10.1016/j.ipm.2020.102439
Scopus ID
85097135894
ISSN
03064573
Authors
5
Open access
No
Citations
325
International co-authorship
Yes
Co-author countries
ES, GB, IN, SA

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

    GoalPrimaryHigh confidenceJudged

    Graph convolutional network and CNN hybrid model achieving 96.1% accuracy for breast cancer classification enabling early disease detection

    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. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-1.2 Health and well-being

    Sub-themePrimaryHigh confidenceJudged

    Artificial intelligence for cancer detection improves health outcomes through automated screening reducing diagnostic time and treatment delay

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

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KIIT Deemed to be University. “Improved Breast Cancer Classification Through Combining Graph Convolutional Network and Convolutional Neural Network”. Kortex.

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