Publication2023
Improved invasive weed bird swarm optimization algorithm (IWBSOA) enabled hybrid deep learning classifier for diabetic prediction
The record
- Type
- Publication
- Date
- 1 April 2023
- Level
- National
- Journal
- Journal of Ambient Intelligence and Humanized Computing
- Volume
- 14
- Issue
- 4
- Pages
- 3929-3945
- Published
- 1 April 2023
- DOI
- 10.1007/s12652-022-04462-z
- Scopus ID
- 85140841989
- ISSN
- 18685137
- Authors
- 2
- Open access
- No
- Citations
- 17
- 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
3.5 Strengthen prevention and treatment of substance abuse, including narcotic drug abuse and harmful use of alcohol
Gene expression-based diabetic prediction using optimized machine learning algorithms enables early disease identification and intervention.
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Hybrid deep learning classifier combining multiple optimization algorithms represents research innovation in computational methods.
- 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
Diabetes prediction technology supports early detection and health management in vulnerable populations.
- 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. “Improved invasive weed bird swarm optimization algorithm (IWBSOA) enabled hybrid deep learning classifier for diabetic prediction”. Kortex.