Publication2025
Edge-Optimized Explainable AI for Medical Image Diagnosis using Hybrid CNN-Transformer Architecture
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 2025 5th IEEE International Conference on Applied Electromagnetics Signal Processing and Communication Aespc 2025
- Published
- 1 January 2025
- DOI
- 10.1109/aespc67542.2025.11326800
- Scopus ID
- 105033143819
- Authors
- 6
- Open access
- No
- Citations
- 3
- 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
3.8 Achieve universal health coverage, including financial risk protection and access to essential medicines
Hybrid CNN-Transformer explainable AI model for medical image diagnosis with Grad-CAM and SHAP interpretability
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Edge computing optimization and interpretable deep learning innovation for clinical decision support
- 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.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Healthcare AI deployment enabling trusted medical image analysis at point-of-care
- 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. “Edge-Optimized Explainable AI for Medical Image Diagnosis using Hybrid CNN-Transformer Architecture”. Kortex.