Publication2026
A Hybrid Evolutionary Algorithm and Fuzzy Choquet Integral Ensemble for Disease Diagnosis
The record
- Type
- Publication
- Date
- 1 March 2026
- Level
- National
- Journal
- Journal of Fuzzy Extension and Applications
- Volume
- 7
- Issue
- 2
- Pages
- 552-575
- Published
- 1 March 2026
- DOI
- 10.22105/jfea.2025.493745.1736
- Scopus ID
- 105043118054
- ISSN
- 27831442
- Authors
- 4
- Open access
- No
- Citations
- 1
- International co-authorship
- No
- Co-author countries
- IN
Classification
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UN Sustainable Development Goals
3 Ensure healthy lives and promote well-being for all at all ages
Hybrid evolutionary algorithm with fuzzy Choquet integral ensemble achieves 89-95% accuracy across multiple disease datasets (lung cancer, diabetes, cardiovascular) for disease diagnosis.
- 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
Novel hybrid ensemble combining CrayFish and Harris Hawk Optimization with fuzzy integral classification advances research innovation in disease prediction methodology.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Machine learning disease diagnosis system directly supports health and well-being through improved clinical decision support.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
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- 1
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Citing this record
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KIIT Deemed to be University. “A Hybrid Evolutionary Algorithm and Fuzzy Choquet Integral Ensemble for Disease Diagnosis”. Kortex.