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Use of Autopsy to Determine Live or Stillbirth: New Approaches in Decision‐support Systems

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Fetal deaths are important cases for forensic medicine, as well as for criminal and civil law. From a legal perspective, the determination of whether a deceased infant was stillborn is a difficult process. Such a determination is generally made during autopsy; however, no standardized procedures for this determination exist. Therefore, new facilitative approaches are needed. In this study, three new support systems based on 10 autopsy parameters were tested for their ability to correctly determine whether deceased infants were alive or stillborn. Performances were analyzed and compared with one another. The artificial neural networks and radial basis function network models had 90% accuracy (the highest among the models tested), 100% sensitivity, and 83.3% specificity. Thus, the models presented here provide additional insights for future studies concerning infant autopsies.
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Keywords: artificial neural networks; autopsy; forensic science; infant; logistic regression; radial basis function network; support system

Document Type: Research Article

Publication date: March 1, 2017

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