Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning
- DOI
- 10.1016/j.ebiom.2024.105276
- Published
- 2024-09
- Container
- eBioMedicine
- Publisher
- Elsevier BV
- Open access
- unknown
Credibility signals
uncertain Score 64/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- supportingDOI registered: A matching record was returned by Crossref.
- supportingDOI resolves: A matching record was returned by Crossref.
- 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.
- supportingMetadata completeness: All 6 scored descriptive metadata groups are present.
Cite this work
BibTeX
@article{allodium:10.1016/j.ebiom.2024.105276,
title = {Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning},
author = {Divya Choudhury and James M. Dolezal and Emma Dyer and Sara Kochanny and Siddhi Ramesh and Frederick M. Howard and Jayson R. Margalus and Amelia Schroeder and Jefree Schulte and Marina C. Garassino and Jakob N. Kather and Alexander T. Pearson},
year = {2024},
journal = {eBioMedicine},
doi = {10.1016/j.ebiom.2024.105276},
url = {https://doi.org/10.1016/j.ebiom.2024.105276}
}RIS
TY - JOUR TI - Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning AU - Divya Choudhury AU - James M. Dolezal AU - Emma Dyer AU - Sara Kochanny AU - Siddhi Ramesh AU - Frederick M. Howard AU - Jayson R. Margalus AU - Amelia Schroeder AU - Jefree Schulte AU - Marina C. Garassino AU - Jakob N. Kather AU - Alexander T. Pearson PY - 2024 JO - eBioMedicine DO - 10.1016/j.ebiom.2024.105276 UR - https://doi.org/10.1016/j.ebiom.2024.105276 ER -
APA
Choudhury, D., Dolezal, J. M., Dyer, E., Kochanny, S., Ramesh, S., Howard, F. M., Margalus, J. R., Schroeder, A., Schulte, J., Garassino, M. C., Kather, J. N., & Pearson, A. T. (2024). Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning. eBioMedicine. https://doi.org/10.1016/j.ebiom.2024.105276
Source records
- crossref · retrieved 2026-09-27T13:39:26.197Z