Cross Reference Down
Plesničar, AF, Bizjak, NB and Jazbinšek, P (2025). Enhancing Healthcare Integrity Using Simple Statistical Methods: Detecting Irregularities in Historical Dermatology Services Payments. Preprint on Preprints.org.
This work cites the following items of the Benford Online Bibliography:
| Antunes, AM, Teixeira, D and Sousa, F (2023). Benford’s Law: the fraud detection’s left hand. Proceedings of 18th Iberian Conference on Information Systems and Technologies (CISTI), Aveiro, Portugal, pp. 1-6. DOI:10.23919/CISTI58278.2023.10211738. |  |
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| Azevedo, CdS, Gonçalves, RF, Gava, VL and Spinola, MdM (2021). A Benford’s Law based methodology for fraud detection in social welfare programs: Bolsa Familia analysis. Physica A 567, p. 125626. DOI:10.1016/j.physa.2020.125626. | |
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| Bosnjak, M, Dahm, S, Kuhnert, R, Weihrauch, D, Rosario, AS, Hurraß, J, Schmich, P and Wieler, LH (2024). Potential COVID-19 test fraud detection: Findings from a pilot study comparing conventional and statistical approaches. Journal of Health Monitoring 9(2), pp. e12100. DOI:10.25646/12100. | |
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| Goh, C (2020). Applying visual analytics to fraud detection using Benford's law. Journal of Corporate Accounting & Finance, pp. 1-7. DOI:10.1002/jcaf.22440. | |
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| Miller, SJ and Nigrini, MJ (2015). Excel Program to test for Benfordness. Available online. Last accessed July 1, 2020. | |
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| Orita, M, Hagiwara, Y, Moritomo, A, Tsunoyama, K, Watanabe, T and Ohno, K (2013). Agreement of drug discovery data with Benford's law. Expert Opinion on Drug Discovery 8(1), pp. 1-5. DOI:10.1517/17460441.2013.740007. | |
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