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

Publication2025

AI-Driven Quantitative Metabolomics for Early and Precise HIE Diagnosis: Challenges and Solutions

The record

Type
Publication
Date
9 December 2025
Level
National
Journal
ACS Omega
Volume
10
Issue
48
Pages
57876-57888
Published
9 December 2025
DOI
10.1021/acsomega.5c03256
Scopus ID
105035706751
ISSN
24701343
Authors
8
Open access
Yes
Citations
1
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 3.2 End preventable deaths of newborns and children under five years of age

    TargetPrimaryHigh confidenceJudged

    Develops AI-driven metabolomics strategies for early diagnosis of hypoxic-ischemic encephalopathy in neonates, reducing brain injury severity, neonatal mortality, and long-term neurodevelopmental impairment.

    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

    Improves maternal and child health outcomes through early disease diagnosis and intervention.

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

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KIIT Deemed to be University. “AI-Driven Quantitative Metabolomics for Early and Precise HIE Diagnosis: Challenges and Solutions”. Kortex.

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