Publication2021
Variable Optimization in Cervical Cancer Data Using Particle Swarm Optimization
The record
- Type
- Publication
- Date
- 1 January 2021
- Level
- National
- Journal
- Lecture Notes in Electrical Engineering
- Volume
- 709
- Pages
- 147-153
- Published
- 1 January 2021
- DOI
- 10.1007/978-981-15-8752-8_15
- Scopus ID
- 85101423678
- ISSN
- 18761100
- Authors
- 5
- Open access
- No
- Citations
- 39
- 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
3.4 Reduce premature mortality from non-communicable diseases and promote mental health and well-being
Particle swarm optimization for cervical cancer feature selection improves machine learning classification of disease progression and diagnostic accuracy.
- 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
Cancer detection and diagnostic improvement support women's health outcomes.
- 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.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “Variable Optimization in Cervical Cancer Data Using Particle Swarm Optimization”. Kortex.