Publication2024
Machine Learning Methods for the Timely Identification of Autism Spectrum Disorder in Toddlers
The record
- Type
- Publication
- Date
- 1 January 2024
- Level
- National
- Journal
- Esic 2024 4th International Conference on Emerging Systems and Intelligent Computing Proceedings
- Pages
- 515-520
- Published
- 1 January 2024
- DOI
- 10.1109/esic60604.2024.10481550
- Scopus ID
- 85191016295
- Authors
- 2
- Open access
- No
- Citations
- 39
- 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
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Machine learning algorithms for early Autism Spectrum Disorder detection in toddlers enable timely intervention improving developmental outcomes.
- 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
4.3 Ensure equal access for all women and men to affordable quality technical, vocational and tertiary education, including university
Early diagnosis of developmental disorders supports educational planning and special needs intervention.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
AI-based early developmental disorder screening directly improves child health and well-being through timely intervention.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Machine Learning Methods for the Timely Identification of Autism Spectrum Disorder in Toddlers”. Kortex.