Publication2024
Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing
The record
- Type
- Publication
- Date
- 1 December 2024
- Level
- International — held abroad
- Journal
- BMC Bioinformatics
- Volume
- 25
- Issue
- 1
- Published
- 1 December 2024
- DOI
- 10.1186/s12859-024-05866-8
- Scopus ID
- 85206373299
- ISSN
- 14712105
- Authors
- 9
- Open access
- Yes
- Citations
- 31
- International co-authorship
- Yes
- Co-author countries
- GB, IN, SA, US
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 stacking ensemble approach achieves 98.6% accuracy in stroke prediction for early intervention and reduced mortality from cerebrovascular disease
- Certain confidence
- The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
- 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
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- 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.
- 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
vb-1.2 Health and well-being
Healthcare analytics using principal component analysis and ensemble methods for preventive diagnosis and patient care strategies
- 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. “Predicting stroke occurrences: a stacked machine learning approach with feature selection and data preprocessing”. Kortex.