Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study.
- DOI
- 10.1016/j.landig.2025.02.008
- Published
- 2025 May
- Container
- The Lancet. Digital health
- Publisher
- Not recorded
- Open access
- unknown
Credibility signals
limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredOpen access status: Not checked or no result supplied; no credibility inference made.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.1016/j.landig.2025.02.008,
title = {Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study.},
author = {Meng Z and Guan Z and Yu S and Wu Y and Zhao Y and Shen J and Lim CC and Chen T and Yang D and Ran AR and He F and Hamzah H and Singh S and Abd Raof AS and Lee-Boey JWS and Lim SK and Sun X and Ge S and Xu G and Su H and Cheng Y and Lu F and Liao X and Jin H and Deng C and Ruan L and Zhang C and Wu C and Dai R and Jin Y and Wang W and Li T and Liu R and Li J and Shu J and Lu Y and Wang X and Wu Q and Qin Y and Tang J and Sheng X and Jiao Q and Yang X and Guo M and McKay GJ and Hogg RE and Liew G and Chee EYL and Hsu W and Lee ML and Szeto S and Luk AOY and Chan JCN and Cheung CY and Tan GSW and Tham YC and Cheng CY and Sabanayagam C and Lim LL and Jia W and Li H and Sheng B and Wong TY},
year = {2025},
journal = {The Lancet. Digital health},
doi = {10.1016/j.landig.2025.02.008},
url = {https://doi.org/10.1016/j.landig.2025.02.008}
}RIS
TY - JOUR TI - Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study. AU - Meng Z AU - Guan Z AU - Yu S AU - Wu Y AU - Zhao Y AU - Shen J AU - Lim CC AU - Chen T AU - Yang D AU - Ran AR AU - He F AU - Hamzah H AU - Singh S AU - Abd Raof AS AU - Lee-Boey JWS AU - Lim SK AU - Sun X AU - Ge S AU - Xu G AU - Su H AU - Cheng Y AU - Lu F AU - Liao X AU - Jin H AU - Deng C AU - Ruan L AU - Zhang C AU - Wu C AU - Dai R AU - Jin Y AU - Wang W AU - Li T AU - Liu R AU - Li J AU - Shu J AU - Lu Y AU - Wang X AU - Wu Q AU - Qin Y AU - Tang J AU - Sheng X AU - Jiao Q AU - Yang X AU - Guo M AU - McKay GJ AU - Hogg RE AU - Liew G AU - Chee EYL AU - Hsu W AU - Lee ML AU - Szeto S AU - Luk AOY AU - Chan JCN AU - Cheung CY AU - Tan GSW AU - Tham YC AU - Cheng CY AU - Sabanayagam C AU - Lim LL AU - Jia W AU - Li H AU - Sheng B AU - Wong TY PY - 2025 JO - The Lancet. Digital health DO - 10.1016/j.landig.2025.02.008 UR - https://doi.org/10.1016/j.landig.2025.02.008 ER -
APA
Z, M., Z, G., S, Y., Y, W., Y, Z., J, S., CC, L., T, C., D, Y., AR, R., F, H., H, H., S, S., AS, A. R., JWS, L., SK, L., X, S., S, G., G, X., H, S., Y, C., F, L., X, L., H, J., C, D., L, R., C, Z., C, W., R, D., Y, J., W, W., T, L., R, L., J, L., J, S., Y, L., X, W., Q, W., Y, Q., J, T., X, S., Q, J., X, Y., M, G., GJ, M., RE, H., G, L., EYL, C., W, H., ML, L., S, S., AOY, L., JCN, C., CY, C., GSW, T., YC, T., CY, C., C, S., LL, L., W, J., H, L., B, S., & TY, W. (2025). Non-invasive biopsy diagnosis of diabetic kidney disease via deep learning applied to retinal images: a population-based study.. The Lancet. Digital health. https://doi.org/10.1016/j.landig.2025.02.008
Source records
- pubmed · retrieved 2026-09-26T17:12:43.230Z