Publication2025
Ultrasound-Based Thyroid Nodule Classification Using GoogleNet and Xception Ensemble with CNN-LSTM Hybridization
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- 8th World Engineering Conference on Contemporary Technologies Wecon 2025 Nextgen Sustainable Technologies
- Published
- 1 January 2025
- DOI
- 10.1109/wecon68556.2025.11414458
- Scopus ID
- 105036701617
- Authors
- 2
- Open access
- No
- Citations
- 0
- 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
Deep learning ensemble for thyroid cancer detection and classification enhances diagnostic accuracy and supports cancer treatment outcomes.
- 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
Hybrid CNN-LSTM architecture for medical image classification advances research capacity in artificial intelligence and healthcare technology.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
AI-assisted cancer diagnosis system directly supports health outcomes through improved detection reliability and timely medical intervention.
- 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. “Ultrasound-Based Thyroid Nodule Classification Using GoogleNet and Xception Ensemble with CNN-LSTM Hybridization”. Kortex.