Publication2023
Anomaly Detection in Medical Images Using Convolutional Neural Networks
- Good Health and Well-being
- Industry, Innovation and Infrastructure
- Empowered Indians
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- Proceedings 2023 IEEE International Conference on Paradigm Shift in Information Technologies with Innovative Applications in Global Scenario Icpsitiags 2023
- Pages
- 54-60
- Published
- 1 January 2023
- DOI
- 10.1109/icpsitiags59213.2023.10527539
- Scopus ID
- 85194132458
- Authors
- 5
- Open access
- No
- Citations
- 1
- 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
Convolutional neural network approaches for detecting anomalies in clinical images enabling rapid disease screening and early 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
Deep learning methodology for medical image analysis advancing artificial intelligence research capacity in biomedical image processing
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Convolutional neural network approaches for detecting anomalies in clinical images enabling rapid disease screening and early diagnosis
- 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. “Anomaly Detection in Medical Images Using Convolutional Neural Networks”. Kortex.