Publication2017
Feature extraction and selection with optimization technique for brain tumor detection from MR images
The record
- Type
- Publication
- Date
- 2 July 2017
- Level
- National
- Journal
- Iccids 2017 International Conference on Computational Intelligence in Data Science Proceedings
- Volume
- 2018-January
- Pages
- 1-7
- Published
- 2 July 2017
- DOI
- 10.1109/iccids.2017.8272635
- Scopus ID
- 85047340182
- Authors
- 3
- Open access
- No
- Citations
- 13
- 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
Feature extraction and optimization with hybrid genetic algorithms detects brain tumors from MR images achieving 0.73 dice similarity coefficient
- 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
Viksit Bharat @2047
vb-1.2 Health and well-being
Brain tumor detection automation improves diagnostic accuracy and treatment planning enabling faster clinical intervention
- 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. “Feature extraction and selection with optimization technique for brain tumor detection from MR images”. Kortex.