Publication2026
A Data Normalized NLP-Based Framework for Improving Patient Care Using Sentiment Analysis
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- International — held abroad
- Journal
- Lecture Notes in Networks and Systems
- Volume
- 1495 LNNS
- Pages
- 113-124
- Published
- 1 January 2026
- DOI
- 10.1007/978-981-96-8043-6_10
- Scopus ID
- 105025742413
- ISSN
- 23673370
- Authors
- 6
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- CN, GB, 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
NLP-based sentiment analysis of patient feedback achieves 94% accuracy for identifying care quality issues and improving patient satisfaction.
- 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
Optimized TF-IDF with transformers advances natural language processing research capacity for healthcare applications.
- 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
Patient-centered healthcare improvement using AI sentiment analysis directly enhances care quality and health service delivery.
- 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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Provenance
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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. “A Data Normalized NLP-Based Framework for Improving Patient Care Using Sentiment Analysis”. Kortex.
