Publication2023
Machine Learning Approaches for Improving the Survival Prediction Rate in Heart Failure Patients
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- Ocit 2023 21st International Conference on Information Technology Proceedings
- Pages
- 508-513
- Published
- 1 January 2023
- DOI
- 10.1109/ocit59427.2023.10430703
- Scopus ID
- 85186706263
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- No
- Co-author countries
- IN
Classification
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UN Sustainable Development Goals
3.8 Achieve universal health coverage, including financial risk protection and access to essential medicines
Machine learning approaches for heart failure survival prediction using dimensionality reduction and minority oversampling improve clinical outcome assessment.
- 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
Feature selection and oversampling methodology demonstrates research innovation in medical machine learning applications.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
AI-based survival prediction supports health outcomes and improved clinical decision-making for cardiac patients.
- 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. “Machine Learning Approaches for Improving the Survival Prediction Rate in Heart Failure Patients”. Kortex.