The DOI matches its Crossref record, with a small difference in title or year; the references it cites are not checked yet.
Optimized drug regimen and chemotherapy scheduling for cancer treatment using swarm intelligence
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These findings mirror challenges reported internationally in virtual care, AI implementation, and workforce transformation initiatives”
From A Scoping Review of Implemented Innovations in Cancer Care: Implications for Pan-Canadian Scaling (2026) · cites this paper as [64]
Citations
The citation lists are queued
They are fetched later and appear here then.
References 18 · Cited by 14
Metadata
- Authors
- Dhieb, N., Abdulrashid, I., Ghazzai, H., & Massoud, Y.
- Affiliations
- Stevens Institute of Technology (US)
- University of Tulsa (US)
- King Abdullah University of Science and Technology (SA)
- Corresponding author
- Massoud, Yehia
- Venue
- Annals of Operations Research
- Published
- 2021-09-01
- Volume
- 320
- Issue
- 2
- Pages
- 757-770
- ISSN
- 0254-5330 (ISSN-L)
- 1572-9338
- OpenAlex
- W3196641167
- Cited by
- 14
- References
- 18
- Citations by year
- 2026: 5 · 2025: 1 · 2024: 4 · 2023: 2 · 2022: 2
- FWCI
- 0.78
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Locations
- Annals of Operations Research (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology) (submittedVersion)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Health Sciences › Medicine › Oncology › Cancer Cells and Metastasis
- Keywords
- chemotherapy schedule, cancer therapy, tumor-immune dynamics, lymphocyte populations, drug dosing optimization, optimal control, particle swarm optimization, drug toxicity, tumor shrinkage
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Optimized drug regimen and chemotherapy scheduling for cancer treatment using swarm intelligence. https://app.cochat.ai/papers/10.1007/s10479-021-04234-6
- The paper
- Dhieb, N., Abdulrashid, I., Ghazzai, H., & Massoud, Y. (2023). Optimized drug regimen and chemotherapy scheduling for cancer treatment using swarm intelligence. Annals of Operations Research. https://doi.org/10.1007/s10479-021-04234-6
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
