Publication2023
A fine tuning approach using modified DenseNet model for skin cancer classification
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- International Journal of Medical Engineering and Informatics
- Volume
- 15
- Issue
- 4
- Pages
- 323-335
- Published
- 1 January 2023
- DOI
- 10.1504/ijmei.2023.132612
- Scopus ID
- 85168653001
- ISSN
- 17550653
- Authors
- 2
- Open access
- No
- Citations
- 11
- 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
Modified-DenseNet201 model for skin cancer classification achieved 95.07% overall accuracy and 97.30% melanoma accuracy.
- 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
Fine-tuned deep convolutional neural network architecture for dermoscopy analysis represents research innovation in medical image classification.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
AI-assisted dermatological diagnosis supports cancer early detection and improved patient outcomes.
- 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. “A fine tuning approach using modified DenseNet model for skin cancer classification”. Kortex.