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

Publication2024

Assessing psychological risks severity level using variants of k-nearest neighbor algorithm

The record

Type
Publication
Date
25 March 2024
Level
International — held abroad
Journal
Aip Conference Proceedings
Volume
2919
Issue
1
Published
25 March 2024
DOI
10.1063/5.0184503
Scopus ID
85190768447
ISSN
0094243X
Authors
4
Open access
Yes
Citations
13
International co-authorship
Yes
Co-author countries
BR, 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

    K-nearest neighbor variant models achieve 89.6% average accuracy in DASS-21 questionnaire analysis to predict anxiety disorder and depression severity levels for mental health assessment.

    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

    Machine learning classification and emotional process analysis methodology advance mental health diagnostic research and AI-assisted psychological assessment.

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

  3. 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

    Mental health screening and disorder severity prediction support early intervention and improved psychological well-being outcomes.

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

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KIIT Deemed to be University. “Assessing psychological risks severity level using variants of k-nearest neighbor algorithm”. Kortex.

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