Swofford H J, Koertner A J, Zemp F, Ausdemore M, Liu A, Salyards M J
U.S. Army Criminal Investigation Laboratory, Defense Forensic Science Center, USA.
U.S. Army Criminal Investigation Laboratory, Defense Forensic Science Center, USA.
Forensic Sci Int. 2018 Jun;287:113-126. doi: 10.1016/j.forsciint.2018.03.043. Epub 2018 Apr 3.
The forensic fingerprint community has faced increasing amounts of criticism by scientific and legal commentators, challenging the validity and reliability of fingerprint evidence due to the lack of an empirically demonstrable basis to evaluate and report the strength of the evidence in a given case. This paper presents a method, developed as a stand-alone software application, FRStat, which provides a statistical assessment of the strength of fingerprint evidence. The performance was evaluated using a variety of mated and non-mated datasets. The results show strong performance characteristics, often with values supporting specificity rates greater than 99%. This method provides fingerprint experts the capability to demonstrate the validity and reliability of fingerprint evidence in a given case and report the findings in a more transparent and standardized fashion with clearly defined criteria for conclusions and known error rate information thereby responding to concerns raised by the scientific and legal communities.
法医指纹学界受到了科学和法律评论家越来越多的批评，他们质疑指纹证据的有效性和可靠性，因为缺乏一个基于实证的可证明基础来评估和报告特定案件中证据的强度。本文介绍了一种作为独立软件应用程序开发的方法，即FRStat，它提供了对指纹证据强度的统计评估。使用各种匹配和不匹配的数据集对其性能进行了评估。结果显示出强大的性能特征，其值通常支持特异性率大于99%。这种方法使指纹专家能够在特定案件中证明指纹证据的有效性和可靠性，并以更透明和标准化的方式报告结果，为结论制定明确的标准并提供已知的错误率信息，从而回应科学和法律界提出的担忧。
