The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
From the Bench to the Field in Low‐Cost Diagnostics: Two Case Studies
Open accessAbstract
Despite the growth of research in universities on point‐of‐care (POC) diagnostics for global health, most devices never leave the laboratory. The processes that move diagnostic technology from the laboratory to the field—the processes intended to evaluate operation and performance under realistic conditions—are more complicated than they might seem. Two case studies illustrate this process: the development of a paper‐based device to measure liver function, and the development of a device to identify sickle cell disease based on aqueous multiphase systems (AMPS) and differences in the densities of normal and sickled cells. Details of developing these devices provide strategies for forming partnerships, prototyping devices, designing studies, and evaluating POC diagnostics. Technical and procedural lessons drawn from these experiences may be useful to those designing diagnostic tests for developing countries, and more generally, technologies for use in resource‐limited environments.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Measuring agreement in method comparison studies
Bland, J. M., & Altman, D. G. (1999) · Statistical Methods in Medical Research · doi:10.1177/096228029900800204 · Cited by 9,619
Power failure: why small sample size undermines the reliability of neuroscience
Button, K. S., Ioannidis, J. P. A., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S. J., & Munafò, M. R. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3475 · Cited by 7,641
Introduction to sample size determination and power analysis for clinical trials
Lachin, J. M. (1981) · Controlled Clinical Trials · doi:10.1016/0197-2456(81)90001-5 · Cited by 1,012
Error bars in experimental biology
Cumming, G., Fidler, F., & Vaux, D. L. (2007) · The Journal of Cell Biology · doi:10.1083/jcb.200611141 · Cited by 940
Point-of-care tests for diagnosing infections in the developing world
Peeling, R. W., & Mabey, D. (2010) · Clinical Microbiology and Infection · doi:10.1111/j.1469-0691.2010.03279.x · Cited by 500
Glasgow, R. E., Magid, D. J., Beck, A., Ritzwoller, D., & Estabrooks, P. A. (2005) · Medical Care · doi:10.1097/01.mlr.0000163645.41407.09 · Cited by 308
Cited by
Enzyme‐Based Glucose Sensor: From Invasive to Wearable Device
Lee, H., Hong, Y. J., Baik, S., Hyeon, T., & Kim, D. (2018) · Advanced Healthcare Materials · doi:10.1002/adhm.201701150 · Cited by 778
Origami multiple paper-based electrochemical biosensors for pesticide detection
Arduini, F., Cinti, S., Caratelli, V., Amendola, L., Palleschi, G., & Moscone, D. (2019) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2018.10.014 · Cited by 322
Metadata
- Authors
- Kumar, A. A., Hennek, J. W., Smith, B. S., Kumar, S., Beattie, P., Jain, S., Rolland, J. P., Stossel, T. P., Chunda‐Liyoka, C., & Whitesides, G. M.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2015-04-27
- Volume
- 54
- Issue
- 20
- Pages
- 5836-5853
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2125670534
- Cited by
- 163
- References
- 6
- FWCI
- 10.22
- Type
- journal article
- Language
- en
- Open access
- green
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 ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: From the Bench to the Field in Low‐Cost Diagnostics: Two Case Studies. https://app.cochat.ai/papers/10.1002/anie.201411741
- The paper
- Kumar, A. A., Hennek, J. W., Smith, B. S., Kumar, S., Beattie, P., Jain, S., Rolland, J. P., Stossel, T. P., Chunda‐Liyoka, C., & Whitesides, G. M. (2015). From the Bench to the Field in Low‐Cost Diagnostics: Two Case Studies. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201411741
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.