Funded project2024
Development of Electronic Medical Record (EMR) registry and machine learning model for prediction of diabetic nephropathy using renal biomarkers and clinical data
- Good Health and Well-being
- Industry, Innovation and Infrastructure
- Empowered Indians
The record
- Type
- Funded project
- Date
- 4 April 2024
- School
- Reporting cycle
- 2024
- Nature
- Ongoing Research
- Sanctioned
- 4 April 2024
- Funding agency
- ICMR
- Sanction reference
- BMI/Adhoc/27/2022-23
- Investigators
- 1
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
Medical research council project building an electronic medical record registry and machine learning model to predict diabetic nephropathy.
- Certain confidence
- The record states the subject matter explicitly. A reader shown only the title and this goal would agree without hesitation. Example: a workshop titled "Renewable Energy and Smart Grid" against SDG 7.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-opus-5[1m], under kortex-input-v1+rubric@1.1.0#7bc5877481c9Input template kortex-input-v1; rubric 1.1.0. Each can change without the others, which is why the version is a composite.
9 Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation
Medical research council project building an electronic medical record registry and machine learning model to predict diabetic nephropathy.
- 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-opus-5[1m], under kortex-input-v1+rubric@1.1.0#7bc5877481c9Input template kortex-input-v1; rubric 1.1.0. Each can change without the others, which is why the version is a composite.
Viksit Bharat @2047
vb-1 Empowered Indians
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 3 label. Medical research council project building an electronic medical record registry and machine learning model to predict diabetic nephropathy.
- Produced by
- claude-opus-5[1m], under kortex-input-v1+rubric@1.1.0#7bc5877481c9Input template kortex-input-v1; rubric 1.1.0. Each can change without the others, which is why the version is a composite.
Records of this type were classified by individual judgment against the published rubric, over 1,101 activities. Each label above carries the rubric version it was produced under. How each classification is reached.
Evidence
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Provenance
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- Source rows resolved into this record
- 1
- Source records held
- 1
| Source system | Reference | Last read |
|---|---|---|
| KIIT PBAS reporting workbook, 2024 cycle | Project & Consultancy - 2024!52 |
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KIIT Deemed to be University. “Development of Electronic Medical Record (EMR) registry and machine learning model for prediction of diabetic nephropathy using renal biomarkers and clinical data”. Kortex. Last read 17 September 2026.