Publication2026
Multimodal deep feature fusion with transformer for brain tumor classification from magnetic resonance imaging
The record
- Type
- Publication
- Date
- 1 December 2026
- Level
- National
- Journal
- Scientific Reports
- Volume
- 16
- Issue
- 1
- Published
- 1 December 2026
- DOI
- 10.1038/s41598-026-44957-9
- Scopus ID
- 105040731593
- ISSN
- 20452322
- Authors
- 7
- Open access
- Yes
- 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
Develops multimodal deep learning framework for automated brain tumor detection and segmentation from MRI achieving 98.91% accuracy for precise 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
Research on deep learning and transformer networks for medical image analysis contributes to advancing AI research capacity in healthcare applications.
- 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
Advanced AI technology for cancer diagnosis directly enhances health outcomes and therapeutic precision in oncology management.
- 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. “Multimodal deep feature fusion with transformer for brain tumor classification from magnetic resonance imaging”. Kortex.