Publication2023
Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- International — held abroad
- Journal
- Computers and Electrical Engineering
- Volume
- 105
- Published
- 1 January 2023
- DOI
- 10.1016/j.compeleceng.2022.108479
- Scopus ID
- 85143832558
- ISSN
- 00457906
- Authors
- 7
- Open access
- No
- Citations
- 34
- International co-authorship
- Yes
- Co-author countries
- AE, IN, SA, US
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
Dense convolutional neural network with novel loss function achieves 93.78% prediction accuracy for COVID-19 detection in computed tomography scans.
- 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 model optimization and loss function innovation advance diagnostic imaging methodology.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Rapid COVID-19 diagnosis enables timely treatment and infection control measures.
- 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. “Enhanced framework for COVID-19 prediction with computed tomography scan images using dense convolutional neural network and novel loss function”. Kortex.