Publication2018
Implementation of biologically motivated optimisation approach for tumour categorisation
The record
- Type
- Publication
- Date
- 1 January 2018
- Level
- National
- Journal
- International Journal of Computer Aided Engineering and Technology
- Volume
- 10
- Issue
- 3
- Pages
- 244-256
- Published
- 1 January 2018
- DOI
- 10.1504/ijcaet.2018.10011576
- Scopus ID
- 85044351018
- ISSN
- 17572657
- Authors
- 3
- Open access
- No
- Citations
- 33
- 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
Bio-inspired optimization techniques including genetic search and PSO classify tumor types with enhanced accuracy using multilayer perceptron networks for cancer 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
Viksit Bharat @2047
vb-1.2 Health and well-being
Machine learning approaches for tumor categorization improve cancer classification accuracy supporting clinical diagnostic decision-making in oncology.
- 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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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Implementation of biologically motivated optimisation approach for tumour categorisation”. Kortex.