Conceptio
›
Archive
›
The University of Melbourne Library Digital Repository
The University of Melbourne Library Digital Repository
metadata only
Author Correction: A machine learning driven nomogram for predicting chronic kidney disease stages 3–5 (Scientific Reports, (2023), 13, 1, (21613), 10.1038/s41598-023-48815-w)
Ghosh, SK et al.
The University of Melbourne Library Digital Repository · Papers
Open Source ↗
academic, research
This document is indexed with metadata only — full text is not available in the archive for this record.
Open the official source ↗
Related documents
How can countries respond to the health and care workforce crisis? Insights from international evidence
#1005618
Management of patients with advanced prostate cancer: Recommendations of the St Gallen Advanced Prostate Cancer Consensus Conference (APCCC) 2015
#1005619
A high-throughput method using Ultra-Performance Liquid Chromatography to determine water-soluble carbohydrate concentrations in pasture plants
#1005621
Malaria case management in Papua New Guinea prior to the introduction of a revised treatment protocol
#1005622
Connectivity-guided, interleaved iTBS-fMRI demonstrates subcortical target engagement in treatment-resistant depression
#1005623
Record
· ID 1005454
Retrieved via
Conceptio
— every document is proof-bundled with source, license, and retrieval metadata.