Publication2023
Impact of Machine Intelligence on Clinical Disease Outbreak Prediction
The record
- Type
- Publication
- Date
- 1 January 2023
- Level
- National
- Journal
- 2023 10th IEEE Uttar Pradesh Section International Conference on Electrical Electronics and Computer Engineering Upcon 2023
- Pages
- 1020-1025
- Published
- 1 January 2023
- DOI
- 10.1109/upcon59197.2023.10434492
- Scopus ID
- 85187352329
- Authors
- 5
- Open access
- No
- Citations
- 5
- 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
3.3 End the epidemics of AIDS, tuberculosis, malaria, neglected tropical diseases, hepatitis and water-borne diseases
AI techniques for disease outbreak prediction assess infectious diseases, vector-borne diseases and epidemics enabling proactive public health interventions and response.
- 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
Machine learning methodology for disease prediction research represents healthcare informatics and AI innovation.
- 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
Viksit Bharat @2047
vb-1.2 Health and well-being
AI-based epidemic prediction supports disease prevention and population health surveillance 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
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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. “Impact of Machine Intelligence on Clinical Disease Outbreak Prediction”. Kortex.