Publication2023
Segmentation-Based Classification Deep Learning Model for Breast Cancer Detection using Mammogram images
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- 2023 IEEE 3rd Mysore Sub Section International Conference Mysurucon 2023
- Published
- 1 January 2023
- DOI
- 10.1109/mysurucon59703.2023.10397015
- Scopus ID
- 85184802723
- Authors
- 4
- 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
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Develops segmentation-based deep learning model achieving 98.75% accuracy for automated breast cancer detection from mammogram images in clinical screening.
- 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
Automated cancer detection system improves health and well-being by enabling early breast cancer diagnosis and reducing diagnostic error rates.
- 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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Provenance
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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. “Segmentation-Based Classification Deep Learning Model for Breast Cancer Detection using Mammogram images”. Kortex.
