Publication2025
Enhancing Breast Cancer Detection Using SVM and Explainable AI
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 5th International Conference on Emerging Research in Electronics Computer Science and Technology Icerect 2025
- Published
- 1 January 2025
- DOI
- 10.1109/icerect65215.2025.11376239
- Scopus ID
- 105034851499
- Authors
- 9
- Open access
- No
- Citations
- 0
- 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
SVM-based classification model achieves 98.25% accuracy for early breast cancer detection distinguishing malignant from benign tumors in diagnostic imaging.
- 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
Machine learning methodology development including explainable AI techniques like LIME and SHAP for model interpretability in medical diagnostics.
- 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
Early cancer detection directly improves diagnostic outcomes and patient treatment pathways for health and well-being.
- 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. “Enhancing Breast Cancer Detection Using SVM and Explainable AI”. Kortex.