Publication2023
Detection of Abnormalities in Chest X-Rays Using Convolutional Neural Networks
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
- 123-129
- Published
- 1 January 2023
- DOI
- 10.1109/icpsitiags59213.2023.10527689
- Scopus ID
- 85194149332
- Authors
- 6
- Open access
- No
- Citations
- 0
- 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 Ensure healthy lives and promote well-being for all at all ages
Convolutional neural network model for automated chest X-ray abnormality detection achieving 97.2% accuracy supports radiologist workflow and enables early disease identification.
- 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-3.2 Digital technology and artificial intelligence
Deep learning application in medical imaging represents digital technology innovation for healthcare diagnostics.
- 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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- 1
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Citing this record
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KIIT Deemed to be University. “Detection of Abnormalities in Chest X-Rays Using Convolutional Neural Networks”. Kortex.