Publication2025
Development of an electronic medical record (EMR) registry and machine learning (ML) model for prediction of diabetic kidney disease (DKD) using clinical data
The record
- Type
- Publication
- Date
- 1 January 2025
- Level
- National
- Journal
- International Journal of Diabetes in Developing Countries
- Published
- 1 January 2025
- DOI
- 10.1007/s13410-025-01552-4
- Scopus ID
- 105017506643
- ISSN
- 09733930
- Authors
- 5
- Open access
- No
- Citations
- 0
- 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
Machine learning model with 81.11% accuracy and 0.86 AUC-ROC for predicting diabetic kidney disease from clinical EMR data directly improves identification of at-risk patients and supports preventive healthcare interventions.
- 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
AI innovation for disease prediction using SHAP explainability advances research capacity in machine learning applications for clinical decision support.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-1.2 Health and well-being
Predictive model for diabetic kidney disease enables early identification and preventive treatment, improving health outcomes for diabetes 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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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “Development of an electronic medical record (EMR) registry and machine learning (ML) model for prediction of diabetic kidney disease (DKD) using clinical data”. Kortex.